Novel VAMPIRE algorithms for quantitative analysis of the retinal vasculature

This paper summarizes three recent, novel algorithms developed within VAMPIRE, namely optic disc and macula detection, arteryvein classification, and enhancement of binary vessel masks, and their performance assessment. VAMPIRE is an international collaboration growing a suite of software tools to allow efficient quantification of morphological properties of the retinal vasculature in large collections of fundus camera images. VAMPIRE measurements are currently mostly used in biomarker research, i.e., investigating associations between the morphology of the retinal vasculature and a number of clinical and cognitive conditions.

A modeling study suggesting how a reduction in the context-dependent input on CA1 pyramidal neurons could generate schizophrenic behavior.

The neural mechanisms underlying schizophrenic behavior are unknown and very difficult to investigate experimentally, although a few experimental and modeling studies suggested possible causes for some of the typical psychotic symptoms related to this disease. The brain region most involved in these processes seems to be the hippocampus, because of its critical role in establishing memories for objects or events in the context in which they occur. In particular, a hypofunction of the N-methyl-D-aspartate (NMDA) component of the synaptic input on the distal dendrites of CA1 pyramidal neurons has been suggested to play an important role for the emergence of schizophrenic behavior. Modeling st…

PICTORIAL-C LANGUAGE FOR THE HERMIA-MACHINE

The design and implementation of algorithms on multi-processors machines is hard. The paper describes the general features of the Pictorial C Language (PICL) that is oriented to image analysis. Its integration in the software environment of the HERMIA machine, and the handling of the related interconnecting network topology is also given.

Measurement of the energy spectrum of cosmic rays above 10^18 eV using the Pierre Auger Observatory

We report a measurement of the flux of cosmic rays with unprecedented precision and Statistics using the Pierre Auger Observatory Based on fluorescence observations in coincidence with at least one Surface detector we derive a spectrum for energies above 10(18) eV We also update the previously published energy spectrum obtained with the surface detector array The two spectra are combined addressing the systematic uncertainties and, in particular. the influence of the energy resolution on the spectral shape The spectrum can be described by a broken power law E-gamma with index gamma = 3 3 below the ankle which is measured at log(10)(E-ankle/eV) = 18 6 Above the ankle the spectrum is describe…

Approximated overlap error for the evaluation of feature descriptors on 3D scenes

This paper presents a new framework to evaluate feature descriptors on 3D datasets. The proposed method employs the approximated overlap error in order to conform with the reference planar evaluation case of the Oxford dataset based on the overlap error. The method takes into account not only the keypoint centre but also the feature shape and it does not require complex data setups, depth maps or an accurate camera calibration. Only a ground-truth fundamental matrix should be computed, so that the dataset can be freely extended by adding further images. The proposed approach is robust to false positives occurring in the evaluation process, which do not introduce any relevant changes in the …

Restoration of Vertical Line Scratches with a Distributed Genetic Algorithm

This contribution approaches the problem of scratch restoration in old movies as a optimisation's problem. The functional based on the statistical properties of the image around the scratch is optimised using an ad-hoc genetic algorithm. Given the large amount of the computational time needed by genetic algorithms, a network of standard workstations with heterogeneous operating systems has been used. Each workstation in the network works on each scratch to perform the restoration, and a specific machine works as root node with the task of distributing jobs on the network and adding the outputted restored scratches back into the image.

Tecsis: Low-Cost Methodology To Distinguish Archaeological Findings

The automatic or semi-automatic research of archaeological findings includes some methodologies and algorithms of the Computer Vision. Reconstruction of a scene is one of the key step to get the solution to that challenge. This paper will address a methodology to reconstruction underwater scenes with mosaicing techniques. The reconstruction of scene will be the video-mosaic of sea bottom landscapes starting from single video frames. The methodology is based on the evaluation of the optic °ow in between frames, and its motion estimation has been evaluated on the extracted features from the common areas of consecutive pairs frames. This approach carried out the motion model from a geometric p…

Elliptical Fourier Descriptors for shape retrieval in biological images

The retrieval of information in a standard database can be obtained in different ways and in some cases a number of steps are necessary to extract the sought for information. More difficulties exist when we are looking for a pictorial information in a database. This paper presents a method for finding an image in a biological database based on elliptical Fourier descriptors. Fourier descriptors are considered here as textual information and a distance function is proposed to evaluate the best result. Fourier descriptors and distance function are used to retrieve image in pictorial database.

Distributed image retrieval on DAISY

The paper describes an application of image retrieval based on DAISY architecture (distributed architecture for intelligent system). The creation of pictorial indexes may require a number of hours depending on the size of the pictorial data base. The problem can become more complex in the case of distributed database systems. In both cases a distributed architecture can be the natural and more efficient solution. DAISY architecture is based on the concept of co-operating behavioral agents supervised by a central engagement module. Preliminary experiments, to evaluate the performance of the system, have been performed on a astronomical database and coral image

HERMIA - GENERAL DESCRIPTION

VAMPIRE: Vessel assessment and measurement platform for images of the REtina

We present VAMPIRE, a software application for efficient, semi-automatic quantification of retinal vessel properties with large collections of fundus camera images. VAMPIRE is also an international collaborative project of four image processing groups and five clinical centres. The system provides automatic detection of retinal landmarks (optic disc, vasculature), and quantifies key parameters used frequently in investigative studies: vessel width, vessel branching coefficients, and tortuosity. The ultimate vision is to make VAMPIRE available as a public tool, to support quantification and analysis of large collections of fundus camera images.

M-VIF: A machine-vision based on information fusion

The authors describe a new architecture for machine vision, which is based on information fusion approach. Its general design has been developed by using a formal computation model that integrates three main ingredients of the visual computation: the data, the models, and the algorithms. The hardware design and the software environment of M-VIF are also given. The simulation of M-VIF is under development on the HERMIA-machine.

A distributed architecture for autonomous navigation of robots

The paper shows a distributed architecture for autonomous robot navigation. The architecture is based on three modules that are implemented on separate and interacting agents: the target recognizer, the obsta90cle evaluator and the planner. An adaptive genetic algorithm has been studied to identify mechanisms for reaching the target and for manipulating the 2-directions of the robot; the distributed architecture has been embedded in the DAISY (Distributed Architecture for Intelligent System). Experiments have been carried out using a LEGO intelligent brick.

Stable Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and a Modified Fuzzy C-Means Clustering

In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. Three features are extracted from the tested image. The features are scaled down by a factor of 2 and mapped into a Self-Organizing Map. A modified Fuzzy C-Means clustering algorithm is used to divide the neuron units of the map in 2 classes. The entire image is again input for the Self-Organizing Map and the class of each pixel will be the class of its best matching unit in the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the DRIVE database shows accurate ex…

Graph-based minimal path tracking in the skeleton of the retinal vascular network

This paper presents a semi-automatic framework for minimal path tracking in the skeleton of the retinal vascular network. The method is based on the graph structure of the vessel network. The vascular network is represented based on the skeleton of the available segmented vessels and using an undirected graph. Significant points on the skeleton are considered nodes of the graph, while the edge of the graph is represented by the vessel segment linking two neighboring nodes. The graph is represented then in the form of a connectivity matrix, using a novel method for defining vertex connectivity. Dijkstra and Floyd-Warshall algorithms are applied for detection of minimal paths within the graph…

The role of network connectivity on epileptiform activity.

AbstractA number of potentially important mechanisms have been identified as key players to generate epileptiform activity, such as genetic mutations, activity-dependent alteration of synaptic functions, and functional network reorganization at the macroscopic level. Here we study how network connectivity at cellular level can affect the onset of epileptiform activity, using computational model networks with different wiring properties. The model suggests that networks connected as in real brain circuits are more resistant to generate seizure-like activity. The results suggest new experimentally testable predictions on the cellular network connectivity in epileptic individuals, and highligh…

Pictorial information retrieval with uncertain knowledge

In the paper an integrated pictorial database is described. The design of the data management requires many efforts to preserve consistency and integrity. The retrieval operations are designed to support a uniform view of heterogeneous information including uncertain ones; in this last case, non-standard techniques have to be developed. Applications to astronomical images and an outline of the implementation status are given.

HERMIA: An Heterogeneous and Reconfigurable Machine for Image Analysis

In this paper is described the general architecture of an Heterogeneous and Reconfigurable Machine for Image Analysis (HERMIA); the first prototype of the system has been developed at the University of Palermo. Conventional hardware has been used in order to emulate the machine and evaluate the system performance Preliminary results are presented and discussed.

A system for the automatic measurement of the nuchal translucency thickness from ultrasound video stream of the foetus

Nowadays the measurement of the nuchal translucency thickness is being used as part of routine ultrasound scanning during the end of the first trimester of pregnancy, for the screening of chromosomal defects, as trisomy 21. Currently, the measurement is being performed manually by physicians. The measurement can take a long time for being accomplished, needs to be performed by highly skilled operators, and is prone to errors. Semi-automated methods requires that the user manually selects a region of the image containing the nuchal translucency, procedure that is somewhat time consuming. In this paper we present a complete system prototype that is able to perform the measurement of the nucha…

A non-parametric Scale-based Corner Detector

This paper introduces a new Harris-affine corner detector algorithm, that does not need parameters to locate corners in images, given an observation scale. Standard detectors require to fine tune the values of parameters which strictly depend on the particular input image. A quantitative comparison between our implementation and a standard Harris-affine implementation provides good results, showing that the proposed methodology is robust and accurate. The benchmark consists of public images used in literature for feature detection.

A distributed genetic algorithm for restoration of vertical line scratches

This paper reports a distributed algorithm for the restoration of still frames corrupted by vertical line scratches. The restoration is here approached as an optimisation problem, and is solved using an ad-hoc Genetic Algorithm. The distributed algorithm is designed following a pipeline logical structure. The front end is a network of standard workstations with heterogeneous operating systems. The quality of image is appreciable and the computational time is quite low with respect the sequential version.

Visual Tools in Virtual Reality: Complex Environment

In this paper, we analyse an integrated system able to merge graphical and vision technique in order to improve virtual space environment. Virtual space is characterized by Dynamic Visual Icons and Virtual Reality for arising a hererogeneous environment. Essentially, we propose a fusion technique between visual icon and virtual space, where their integration is supported by Visual lcon Grammar (VIG) working on Dynamic lcon and Visual World. VIG allows to test the actions of the Dynamic Icon on the active Visual Word metaphor at the lime "t", and the different rage of transactions between user and VW(visual query, view and brows of under-world,... ). Moreover, user can define, modify and rem…

Analysis of low-correlated spatial gene expression patterns: A clustering approach in the mouse brain data hosted in the Allen Brain Atlas

The Allen Brain Atlas (ABA) provides a similar gene expression dataset by genome-scale mapping of the C57BL/6J mouse brain. In this study, the authors describe a method to extract the spatial information of gene expression patterns across a set of 1047 genes. The genes were chosen from among the 4104 genes having the lowest Pearson correlation coefficient used to compare the expression patterns across voxels in a single hemisphere for available coronal and sagittal volumes. The set of genes analysed in this study is the one discarded in the article by Bohland et al. , which was considered to be of a lower consistency, not a reliable dataset. Following a normalisation task with a global and …

Fusion of visual tools in virtual spaces

Virtual space environment may be improved by combining it with graphical and visual tools. This paper analyses an integrated system able to merge fusion techniques, icons tools and a virtual space environment. A virtual space is characterised by a set of dynamic visual icons and by a heterogeneous virtual reality environment. Their integration is supported by virtual icon grammar (VIG) working on dynamic icons and virtual world. VIG allows to test the actions made by dynamic icons on the activated Virtual World metaphors at a time “t”, and a range of different transactions that place between user and VW(visual query, view and browse of under-world,...), moreover, user can define, modify and…

Exudates as Landmarks Identified through FCM Clustering in Retinal Images

The aim of this work was to develop a method for the automatic identification of exudates, using an unsupervised clustering approach. The ability to classify each pixel as belonging to an eventual exudate, as a warning of disease, allows for the tracking of a patient&rsquo

E-LEARNING AND ART OF PROGRAMMING: A CONTEXT ORIENTED TO

Coding or programming is very important for a number of tasks and this is true not only in problem solving but also in the computer science and over. Many skills have to be acquired before to have a high familiarity degree with this science. In the studies for methods of coding, students have a great problem for understanding on how to solve and to develop algorithms in a rational way, thus the expertise on how to solve and to develop algorithms is the most difficult to acquire for all students in whatever age. This paper introduces the prototype of a framework able to running in the web space and to be supported by different devices and browsers, useful to integrate a number of collaborati…

Visual dynamic environment for distributed systems

Algorithms, based on information fusion, are often embodied in visual perception systems. Distributed architectures have been recently proposed to perform integrated computation. The complexity of distributed systems regards both their design, and the software environment to develop applications. Visual and iconic programming style intends to provide expressive tools to implement, to debug, and to execute programs in distributed environment. Multi-layers graphs languages seem suitable to handle such complexity. This paper describes the design of a visual dynamic environment (VDE), which is based on a graph-grammar. A new class of dynamic visual interfaces is also introduced, and its propert…

The Lateral Trigger Probability function for the Ultra-High Energy Cosmic Ray Showers detected by the Pierre Auger Observatory

In this paper we introduce the concept of Lateral Trigger Probability (LTP) function, i.e., the probability for an Extensive Air Shower (EAS) to trigger an individual detector of a ground based array as a function of distance to the shower axis, taking into account energy, mass and direction of the primary cosmic ray. We apply this concept to the surface array of the Pierre Auger Observatory consisting of a 1.5 km spaced grid of about 1600 water Cherenkov stations. Using Monte Carlo simulations of ultra-high energy showers the LTP functions are derived for energies in the range between 1017 and 1019 eV and zenith angles up to 65. A parametrization combining a step function with an exponenti…

A low level image analysis approach to starfish detection

Experiments on Concurrent Artificial Environment

We show how the simulation of concurrent system is of interest for both behavioral studies and strategies of learning applied on prey-predator problems. In our case learning studies into unknown environment have been applied to mobile units by using genetic algorithms (GA). A set of trajectories, generated by GA, are able to build a description of the external scene driving a predators to a prey. Here, an example of prey-predator strategy,based on field of forces, is proposed. The evolution of the corespondent system can be formalized as an optimization problem and, for that purpose, GA can be use to give the right solution at this problem. This approach could be applied to the autonomous r…

A REST-based framework to support non-invasive and early coeliac disease diagnosis

The health sector has traditionally been one of the early adopters of databases, from the most simple Electronic Health Record (formerly Computer-Based Patient Record) systems in use in general practice, hospitals and intensive care units to big data, multidata based systems used to support diagnosis and care decisions. In this paper we present a framework to support non-invasive and early diagnosis of coeliac disease. The proposed framework makes use of well-known technologies and techniques, both hardware and software, put together in a novel way. The main goals of our framework are: (1) providing users with a reliable and fast repository of a large amount of data; (2) to make such reposi…

An Integrated Environment for Dynamic Processes in distributed Image Analysis System

Distributed systems, sharing same network, are composed by multiple high-performance microcomputers. To improve the performance of such system is necessary to distribute the occurred processes following a suitable approach. To do that, a set of parameters and two composed objects (Tablet and Bonnet: in brief, an extended task and an asynchronous worker respectively) have been defined to satisfy the distribution the tasks. These objects allow to arrange the distribution of processes and data, on the processors, in static and dynamic way. An high level interactive iconic environment, with a set of visual tools, has been developed to improve the management of the resource and to execute the ac…

Semi-automatic registration of retinal images based on line matching approach

Accurate retinal image registration is essential to track the evolution of eye-related diseases. We propose a semiautomatic method based on features relying upon retinal graphs for temporal registration of retinal images. The features represent straight lines connecting vascular landmarks on the retina vascular tree: bifurcations, branchings, crossings, end points. In the built retinal graph, one straight line between two vascular landmarks indicates that they are connected by a vascular segment in the original retinal image. The locations of the landmarks are manually extracted to avoid the information loss due to errors in a retinal vessels segmentation algorithms. A straight line model i…

Single neuron binding properties and the magical number 7

When we observe a scene, we can almost instantly recognize a familiar object or can quickly distinguish among objects differing by apparently minor details. Individual neurons in the medial temporal lobe of humans have been shown to be crucial for the recognition process, and they are selectively activated by different views of known individuals or objects. However, how single neurons could implement such a sparse and explicit code is unknown and almost impossible to investigate experimentally. Hippocampal CA1 pyramidal neurons could be instrumental in this process. Here, in an extensive series of simulations with realistic morphologies and active properties, we demonstrate how n radial (ob…

An Integrated Method for Image Retrieval

This paper presents an information fusion method for image retrieval; the retrieval strategy is based on statistical and geometrical features extracted from sub-images. Our goal is to find a set of best similar images related to a prototype image; this goal may be obtained according to image content rather than symbolic attributes. MRI (Magnetic Resonance Imaging) images and astronomical images have been adopted to test the method. Main steps of the procedure to retrieve images are: (l) Segmentation, (2) Matching, and (3) Decision. The first step involves four clusters co-operating segmentation algorithms; in the matching step, a sets of candidate similar images is provided; finally an info…

Measurement of the Proton-Air Cross Section ats=57  TeVwith the Pierre Auger Observatory

We report a measurement of the proton-air cross section for particle production at the center-of-mass energy per nucleon of 57 TeV. This is derived from the distribution of the depths of shower maxima observed with the Pierre Auger Observatory: systematic uncertainties are studied in detail. Analyzing the tail of the distribution of the shower maxima, a proton-air cross section of [505 +/- 22(stat)(-36)(+28)(syst)] mb is found.

A Medium Level Language for Pyramid Architectures

In the paper a Parallel C Languages for pyramid architectures is described. The concept of context is introduced in order to handle concurrence between processes in massive parallel machines. Feature implementation on the PAPIA-machine are given.

A Binary Particle Swarm Optimization Algorithm for a Double Auction Market

In this paper, we shall show the design of a multi-unit double auction (MDA) market. It should be enough robust, flexible and sufficiently efficient in facilitating exchanges. In a MDA market, sellers and buyers submit respectively asks and bids. A trade is made if a buyers bid exceeds a sellers ask. A sellers ask may match several buyers bids and a buyers bid may satisfy several sellers asks. The trading rule of a market defines the organization, information exchange process, trading procedure and clearance rules of the market. The mechanism is announced before the opening of the market so that every agent knows how the market will operate in advance. These autonomous agents pursue their o…

New Error Measures to Evaluate Features on Three-Dimensional Scenes

In this paper new error measures to evaluate image features in three-dimensional scenes are proposed and reviewed. The proposed error measures are designed to take into account feature shapes, and ground truth data can be easily estimated. As other approaches, they are not error-free and a quantitative evaluation is given according to the number of wrong matches and mismatches in order to assess their validity

A non-parametric segmentation methodology for oral videocapillaroscopic images

We aim to describe a new non-parametric methodology to support the clinician during the diagnostic process of oral videocapillaroscopy to evaluate peripheral microcirculation. Our methodology, mainly based on wavelet analysis and mathematical morphology to preprocess the images, segments them by minimizing the within-class luminosity variance of both capillaries and background. Experiments were carried out on a set of real microphotographs to validate this approach versus handmade segmentations provided by physicians. By using a leave-one-patient-out approach, we pointed out that our methodology is robust, according to precision-recall criteria (average precision and recall are equal to 0.9…

Dynamic interface for machine vision systems

Iconic programming intends to provide expressive tools to implement, to debug, and to execute programs. For this purpose, visual languages need pictorial constructs and metaphors to guide the design of algorithms in interactive fashion. In the paper a new class of dynamic visual interfaces, named DIVA (Dynamic Interface for Visual Applications), is introduced, its properties are described, and an application to visual compilers in a multi-processors system dedicated to image analysis is given. Moreover, a formal definition of dynamic icon (DI) is also given.

Differential diagnostic features of bone marrow biopsies in essential thrombocythemia

Essential Thrombocythemia (ET) is a chronic myeloproliferative disorder (CMPD) characterized by a high platelet count and originating from a multipotent stem cell. For a long time, according to Polycythaemia Vera Study Group (PVSG) criteria, ET diagnosis has not included histopathological data. Bone Marrow (BM) histology was used only to exclude previous or other subtypes of Ph-CMD or Myelodysplastic syndromes (MDS). In addition, the lack of any cytogenetic or molecular-biological marker has made the discrimination between ET and cases of Reactive Thrombocytosys (RT) without a well known cause quite problematic. Analogously, the distinction of ET from the other Ph- CMPDs with similar clinic…

The iconic interface for the PIctorial C language

Iconic environments intend to provide expressive tools to implement, to debug and to execute programs. Moreover its pictorial constructs guide the user to design algorithms in an interactive fashion. Visual interfaces are especially required whenever programs run on an heterogeneous and reconfigurable multiprocessor system oriented to image analysis. Pictorial tools help the user to control the scope of variables, and the distribution of the tasks into the processors. In this paper, the general design, the visual-syntax, and the implementation of the first prototype of an iconic user interface for the PIctorial C Language (PICL) are described. >

Shape analysis for image retrieval

The main aim of this paper is to describe a method for locating a subimage of a stored image that approximately matches a given query image. This matching can support naive users in accessing an image database according to image contents rather symbolic attributes. The query image can be either composed using painting tools or cuts out of an actual scanned image. Our method is based on the extraction of features from the query image and from the stored images. The following three steps are involved: (l) an ISODATA algorithm is applied to segment (into region) both the query image and the stored images; (2) the normalized moment and geometrica! features are computed from the segmented region…

Comparison of different cooperation strategies in the prey-predator problem

The paper describes two cooperating strategies among several homogeneous agents to reach a given target. In our case we used the prey-predators paradigm in which a set of agents (predators) have the purpose to reach a target (prey). The problem is addressed as an optimization problem that has been faced with two different algorithms (a genetic algorithm and a particle swam optimization algorithm). The two approaches are evaluated by using a simulator for each strategy and the results show that the strategies are very different in terms of prey-predator successes. Genetic algorithm can be used by the prey to solve at the best the problem to reach the lair, otherwise the Particle Swarm Optimi…

Keypoint descriptor matching with context-based orientation estimation

Abstract This paper presents a matching strategy to improve the discriminative power of histogram-based keypoint descriptors by constraining the range of allowable dominant orientations according to the context of the scene under observation. This can be done when the descriptor uses a circular grid and quantized orientation steps, by computing or providing a global reference orientation based on the feature matches. The proposed matching strategy is compared with the standard approaches used with the SIFT and GLOH descriptors and the recent rotation invariant MROGH and LIOP descriptors. A new evaluation protocol based on an approximated overlap error is presented to provide an effective an…

Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and K-Means Clustering

In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. A Self-Organizing Map is trained on a portion of the same image that is tested and K-means clustering algorithm is used to divide the map units in 2 classes. The entire image is again input for the Self-Organizing Map, and the class of each pixel will be the class of the best matching unit on the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the publicly available DRIVE database shows accurate extraction of vessels network and a good agreement between our segm…

Iconic framework for cooperative coding

The description of an innovative framework built on top of Web-based visual programming environment is the primary aim of this contribution. In the last decade, many frameworks oriented to visual languages have been introduced in literature to improve the skill on programming languages, but at the best of our knowledge, no framework has been specially designed to support collaborative work on heterogeneous distributed environments. Therefore, SIRENE introduces a new framework in which beginners and experts can cooperate to develop algorithms by using a visual and iconic paradigm. Students, in the classroom or connected from everywhere, can be involved into the definition of the algorithm, c…

Underwater archaeological mosaicing

Archaeological mosaicing is one of the challenges of the computer vision community and it can be faced in a 2D or 3D approach. This contribution regards a methodology to do a mosaic of an underwater bi-dimensional scene. A number of problems arise from the acquisition of images by a remote operated vehicle. Radial distortion, poor luminosity, cloud water, presence of artefacts are part of the issues that can occur; for instance, the radial distortion has been corrected to improve the quality of the input images. Keypoints detection (through SIFT transform), Singular Value Decomposition, Random Samples Consensus are some of the techniques applied in our method. This contribution regards the …

A New Dissimilarity Measure for Clustering Seismic Signals

Hypocenter and focal mechanism of an earthquake can be determined by the analysis of signals, named waveforms, related to the wave field produced and recorded by a seismic network. Assuming that waveform similarity implies the similarity of focal parameters, the analysis of those signals characterized by very similar shapes can be used to give important details about the physical phenomena which have generated an earthquake. Recent works have shown the effectiveness of cross-correlation and/or cross-spectral dissimilarities to identify clusters of seismic events. In this work we propose a new dissimilarity measure between seismic signals whose reliability has been tested on real seismic dat…

A mathematical approach to automatic megakaryocyte classification

A heterogeneous and reconfigurable machine-vision system

This paper describes a new machine-vision system, a HERMIA heterogeneous and reconfigurable machine for image analysis. The architecture topology of the HERMIA machine is reconfigurable; moreover, the integration of its special modules allows a search for optimal strategies to solve vision problems. The general architecture and the hardware implementation are described. The software environment of the HERMIA machine provides a full iconic interface and a pictorial language oriented to vision in multiprocessor architectures. The preliminary system evaluation and applications are shown. © 1995 Springer-Verlag.

An Iconic Framework for Learning the Art of Programming

The integration of programming teachings, in all levels of education, highlights the need to acquire the art of programming for each individual student through versatile tools based on specific cognitive methods. Diversified linguistic metaphors have to be adopted by the developing frame, in order to highlight the qualities of each student. Therefore, a framework, oriented to learning the art of programming, must foster polychrome constructs representations, a number of data structures and an intuitive interfaces in order to make easier to understand the evolution of the algorithm that have to be developed. The following contribution will present a theoretical formalization of a framework f…

Improving Harris corner selection strategy

This study describes a corner selection strategy based on the Harris approach. Corners are usually defined as interest points for which intensity variation in the principal directions is locally maximised, as response from a filter given by the linear combination of the determinant and the trace of the autocorrelation matrix. The Harris corner detector, in its original definition, is only rotationally invariant, but scale-invariant and affine-covariant extensions have been developed. As one of the main drawbacks, corner detector performances are influenced by two user-given parameters: the linear combination coefficient and the response filter threshold. The main idea of the authors' approa…

Retinal image synthesis through the least action principle

Eye fundus image analysis is a fundamental approach in medical diagnosis and follow-up ophthalmic diagnostics. Manual annotation by experts needs hard work, thus only a small set of annotated vessel structures is available. Examples such as DRIVE and STARE include small sets for training images of fundus image benchmarks. Moreover, there is no vessel structure annotation for a number of fundus image datasets. Synthetic images have been generated by using appropriate parameters for the modeling of vascular networks or by methods developing deep learning techniques and supported by performance hardware. Our methodology aims to produce high-resolution synthetic fundus images alternative to the…

Prey-predator strategies in a multiagent system

This paper describes the prey-predator multiagent system which can be considered as an abstraction of more complex real-world models. Both the prey and the predators are considered as autonomous agents with their own behaviors and perception of the environment. In particular, we propose a simulator which lets study different strategies such as cooperation and individualism. An extensive experiment has been carried out in order to prove the effectiveness of the latter.

Combining fuzzy C-mean and normalized convolution for cloud detection in IR images

An important task for the cloud monitoring in several frameworks is providing maps of the cloud coverage. In this paper we present a method to detect cloudy pixels for images taken from ground by an infra-red camera. The method is a three-steps algorithm mainly based on a Fuzzy C-Mean clustering, that works on a feature space derived from the original image and the output of the reconstructed image obtained via normalized convolution. Experiments, run on several infra-red images acquired under different conditions, show that the cloud maps returned are satisfactory. © 2009 Springer Berlin Heidelberg.

A Comparative Study on Feature Selection for Retinal Vessel Segmentation Using FABC

This paper presents a comparative study on five feature selection heuristics applied to a retinal image database called DRIVE. Features are chosen from a feature vector (encoding local information, but as well information from structures and shapes available in the image) constructed for each pixel in the field of view (FOV) of the image. After selecting the most discriminatory features, an AdaBoost classifier is applied for training. The results of classifications are used to compare the effectiveness of the five feature selection methods.

Comparison of stereo vision techniques for cloud-top height retrieval

This paper presents an ongoing study for the estimation of the cloud-top height by using only geometrical methods. In agreement with some recent studies showing that it is possible to achieve reliable height estimations not only with the classical methods based on radiative transfer, this article includes a comparison of performances of a selected set of vision algorithms devoted to extract dense disparity maps or motion fields from Infra Red stereo image pairs. This collection includes both area-based techniques and an optical flow-based method and the comparison is accomplished by using a set of cloudy scenes selected from the Along-Track Scanning Radiometer (ATSR2) database. The first gr…

Stereo Matching Tecniques for Cloud-top Height Retrieval

This paper presents an ongoing study for the estimation of the cloud-top height by using only geometrical methods. It is based on the hypothesis that an infra-red camera is on board a satellite and pairs of images concern nearly the same scene. Stereo-vision techniques are therefore explored in order to test the methodology for height retrieval and in particular results of several techniques of stereo matching are evaluated. This study includes area-based matching algorithms by implementing the basic versions, without considering any further steps of optimisation to improve the results. Dense depth maps are the final outputs whose reliability is verified by computing error statistics with r…

FABC: Retinal Vessel Segmentation Using AdaBoost

This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…

Spatial graphs and Convolutive Models

In the last two decades, many complex systems have benefited from the use of graph theory, and these approaches have shown robust applicability in the field of finance, computer circuits and in biological systems. Large scale models of brain systems make also a great use of random graph models. Graph theory can be instrumental in modeling the connectivity and spatial distribution of neurons, through a characterization of the relative topological properties. However, all approaches in studying brain function have been so far limited to use experimental constraints obtained at a macroscopic level (e.g. fMRI, EEG, MEG, DTI, DSI). In this contribution, we present a microscopic use (i.e. at the …

VIRES: A distributed open architecture for pictorial database

In this paper we describe VIRES (Visual Information Retrieval Extendible System) an open distributed pictorial database for image retrieval. The retrieval methods, pictorial indexing and data are distributed over the network. VIRES has been designed as an open architecture. The system is based on the concept of distributed model via dictionary in order to reach a good versatility without changing the kernel of VIRES.

Evaluation of the Oral Microcirculation in Patients Undergoing Anti COVID-19 Vaccination: A Preliminary Study

Videocapillaroscopy allows the study of both the morphological and architectural structure of the microcirculation and its hemodynamic conditions; these parameters are directly involved in autoimmune and/or inflammatory pathologies. The purpose of this research, based on capillaroscopy, is to establish whether a patient who receives an anti-COVID 19 vaccine has any changes in their oral microcirculation. A complete capillaroscopic mapping of the oral cavity of the subjects examined was made; the investigated mucosa sites were the following: cheek, labial, chewing-gingival and back of the tongue. This study showed an increase in capillary density from the comparison between the mean labial c…

Automated Detection of Optic Disc Location in Retinal Images

This contribution presents an automated method to locate the optic disc in color fundus images. The method uses texture descriptors and a regression based method in order to determine the best circle that fits the optic disc. The best circle is chosen from a set of circles determined with an innovative method, not using the Hough transform as past approaches. An evaluation of the proposed method has been done using a database of 40 images. On this data set, our method achieved 95% success rate for the localization of the optic disc and 70% success rate for the identification of the optic disc contour (as a circle).

Unsupervised recognition of retinal vascular junction points.

Landmark points in retinal images can be used to create a graph representation to understand and to diagnose not only different pathologies of the eye, but also a variety of more general diseases. Aim of this paper is the description of a non-supervised methodology to distinguish between bifurcations and crossings of the retinal vessels, which can be used in differentiating between arteries and veins. A thinned representation of the binarized image, is used to identify pixels with three or more neighbors. Junction points are classified into bifurcations or crossovers according to their geometrical and topological properties. The proposed approach is successfully compared with the state-of-t…

A Study for Cloud Parameter Retrieval from the IR Cloud Cameras of the AUGER Observatory

The Pierre Auger Observatory operative in Argentina, studies the ultra-high energy cosmic rays with energies above 1018eV. The atmosphere is also monitored by a collection of different instruments. In this paper we present a study on the retrieval of the cloud coverage from the atmospheric monitoring data collected by the four IR cloud cameras placed in the sites of the Observatory. We discuss two different algorithms that supply pixel by pixel cloudiness information in the form of binary masks. The final objective of the study is collecting different algorithms to obtain a reliable set that allow to overcome most of the more frequent ambiguities due to particular cloud configurations and a…

An automated image analysis methodology for classifying megakaryocytes in chronic myeloproliferative disorders

This work describes an automatic method for discrimination in microphotographs between normal and pathological human megakaryocytes and between two kinds of disorders of these cells. A segmentation procedure has been developed, mainly based on mathematical morphology and wavelet transform, to isolate the cells. The features of each megakaryocyte (e.g. area, perimeter and tortuosity of the cell and its nucleus, and shape complexity via elliptic Fourier transform) are used by a regression tree procedure applied twice: the first time to find the set of normal megakaryocytes and the second to distinguish between the pathologies. The output of our classifier has been compared to the interpretati…

Improving SIFT-based descriptors stability to rotations

Image descriptors are widely adopted structures to match image features. SIFT-based descriptors are collections of gradient orientation histograms computed on different feature regions, commonly divided by using a regular Cartesian grid or a log-polar grid. In order to achieve rotation invariance, feature patches have to be generally rotated in the direction of the dominant gradient orientation. In this paper we present a modification of the GLOH descriptor, a SIFT-based descriptor based on a log-polar grid, which avoids to rotate the feature patch before computing the descriptor since predefined discrete orientations can be easily derived by shifting the descriptor vector. The proposed des…

Advanced functionality for radio analysis in the Offline software framework of the Pierre Auger Observatory

The advent of the Auger Engineering Radio Array (AERA) necessitates the development of a powerful framework for the analysis of radio measurements of cosmic ray air showers. As AERA performs ‘‘radio- hybrid’’ measurements of air shower radio emission in coincidence with the surface particle detectors and fluorescence telescopes of the Pierre Auger Observatory, the radio analysis functionality had to be incorporated in the existing hybrid analysis solutions for fluorescence and surface detector data. This goal has been achieved in a natural way by extending the existing Auger Offline software framework with radio functionality. In this article, we lay out the design, highlights and features …

Videocapillaroscopy of the Oral Mucosa in Patients with Diabetic Foot: Possible Diagnostic Role of Microangiopathic Damage?

Introduction: Diabetic foot represents one of the most serious and expensive complications of diabetes and is subject to a high percentage of amputations that are almost always preceded by ulcers ascribable to neuropathy and/or vasculopathy. Videocapillaroscopy (VCS) can be a valuable aid in order to uncover morpho-structural anomalies in the vascular bed, both at the level of the oral mucosa and at the level of the terminal vessels of the lower limb. Materials and methods: Sixty subjects divided into 4 groups were enrolled: 15 healthy subjects; 15 patients with diabetes for more than 10 years without ulcerative foot lesions; 15 patients with neuropathic diabetic foot (clinical diagnosis, M…

On the cellular mechanisms underlying working memory capacity in humans

The cellular processes underlying individual differences in the Working Memory Capacity (WMC) of humans are essentially unknown. Psychological experiments suggest that subjects with lower working memory capacity (LWMC), with respect to subjects with higher capacity (HWMC), take more time to recall items from a list because they search through a larger set of items and are much more susceptible to interference during retrieval. However, a more precise link between psychological experiments and cellular properties is lacking and very difficult to investigate experimentally. In this paper, we investigate the possible underlying mechanisms at the single neuron level by using a computational mod…

A Transputer-Based System for Multi-Stroke Character Recognition

A multi-stroke handwritten character recognition system is presented in this paper. A suitable set of Fourier Descriptors is used as features set to describe each stroke. A man-machine interactive algorithm was utilized to accomplish the learning phase and to recognize unknown samples. A PC based prototype was realized at first to test the system. In order to speed up the recognition process, the design and a first prototype of a Transputer-based system have been realized too. Some preliminary experimental results obtained applying these machines to handwritten numerals are reported in the paper.

Silhouette encoding and synthesis using elliptic Fourier descriptors, and applications to videoconferencing

Abstract This paper investigates the use of elliptic Fourier descriptors as a shape descriptor for encoding the silhouette of a person. Shape descriptors are here used for predicting the shape of silhouettes in missing frames within a sequence. This prediction scheme is applied to the case of generating in-between images in a low frame rate videoconferencing system, where the reconstructed silhouette is used as a binary mask for reducing the computational time for the frame reconstruction.

A search for anisotropy in the arrival directions of ultra high energy cosmic rays recorded at the Pierre Auger Observatory

Observations of cosmic ray arrival directions made with the Pierre Auger Observatory have previously provided evidence of anisotropy at the 99% CL using the correlation of ultra high energy cosmic rays (UHECRs) with objects drawn from the Véron-Cetty Véron catalog. In this paper we report on the use of three catalog independent methods to search for anisotropy. The 2pt–L, 2pt+ and 3pt methods, each giving a different measure of selfclustering in arrival directions, were tested on mock cosmic ray data sets to study the impacts of sample size and magnetic smearing on their results, accounting for both angular and energy resolutions. If the sources of UHECRs follow the same large scale structu…

A multiscale approach to automatic and unsupervised retinal vessel segmentation using Self-Organizing Maps

In this paper an automatic unsupervised method for retinal vessel segmentation is described. Self-Organizing Map, modified Fuzzy C-Means, STAPLE algorithms and majority voting strategy were adopted to identify a segmentation of the retinal vessels. The performance of the proposed method was evaluated on the DRIVE database.

Update on the correlation of the highest energy cosmic rays with nearby extragalactic matter

Data collected by the Pierre Auger Observatory through 31 August 2007 showed evidence for anisotropy in the arrival directions of cosmic rays above the Greisen-Zatsepin-Kuz'min energy threshold, 6 x 10(19) eV. The anisotropy was measured by the fraction of arrival directions that are less than 3.1 degrees from the position of an active galactic nucleus within 75 Mpc (using the Veron-Cetty and Veron 12th catalog). An updated measurement of this fraction is reported here using the arrival directions of cosmic rays recorded above the same energy threshold through 31 December 2009. The number of arrival directions has increased from 27 to 69, allowing a more precise measurement. The correlating…

Flow evaluation of red blood cells in capillaroscopic videos

We aim at describing a non-parametric approach to evaluate blood cells velocity in oral capillascopic videos. The proposed methodology is based on the application of standard optical flow algorithms and it is part of a general environment to support during the diagnostic process for evaluating peripheral microcirculation in real time. We validated our approach versus handmade measurements provided by physicians. Results on real data pointed out that our system returns an output coherent to these latter observations.

Recognizing the Emergent and Submerged Iceberg of the Celiac Disease: ITAMA Project-Global Strategy Protocol.

Coeliac disease (CD) is frequently underdiagnosed with a consequent heavy burden in terms of morbidity and health care costs. Diagnosis of CD is based on the evaluation of symptoms and anti-transglutaminase antibodies IgA (TGA-IgA) levels, with values above a tenfold increase being the basis of the biopsy-free diagnostic approach suggested by present guidelines. This study showcased the largest screening project for CD carried out to date in school children (n=20,000) aimed at assessing the diagnostic accuracy of minimally invasive finger prick point-of-care tests (POCT) which, combined with conventional celiac serology and the aid of an artificial intelligence-based system, may eliminate t…

Integration of a structural features-based preclassifier and a man-machine interactive classifier for a fast multi-stroke character recognition

A transputer-based parallel machine for handwritten character recognition is proposed. An algorithm based on structural features and on a tree classifier was used to accomplish the pre-classification of the unknown sample in order to speed up the recognition process. The algorithm for the final classification is based on the description of the strokes through Fourier descriptors. The learning phase is accomplished through a man-machine interactive process. The proposed system can expand its knowledge base. A special representation of this knowledge base is proposed in order to record a great amount of data in a suitable way. A fast multistroke handwritten isolated character recognition syst…

A naive approach to compose aerial images in a mosaic fashion

There is growing interest in multiple sequence image analysis to represent those data in a new landscape, for instance reconstruction of old films, mosaicing of images. This paper focuses attention on the mosaic problem; it introduces a naive method to link together images where a common part of the scene is present among two images. An application has been developed to test the method on aerial sequences of images. Given the long distance of aircraft from the scene, the method assumes images without distortions and without problems of prospective. Moreover, the application does not need any additional parameters coming from human experience and for this reason it can be thought of as a ful…

A non-supervised approach to locate and to measure the nuchal translucency by means of wavelet analysis and neural networks

Ultrasound imaging is a well known noninvasive way to evaluate various diseases during the prenatal age. In particular, the thickness measure of the nuchal transucency is strictly correlated with pathologies like trisomy 13, 18 and 21. For a correct investigation, the methodology needs mid-sagittal sections and the proposed approach is based on wavelet analysis and neural network classifiers to locate components useful to identify mid-sagittal planes. To evaluate the performance and the robustness of the methodology, real clinical ultrasound images were considered, obtaining an average error of at most 0.3 millimeters in 97.4% of the cases.

A study on recovering the cloud top-height from infra-red video sequences

In this paper we present some preliminary results on an opticalfow based technique aimed at recovering the cloud-top height from infra-red image sequences. The recovery of the cloud-top height from satellite infra-red images is an important topic in meteorological studies, and is traditionally based on the analysis of the temperature maps. In this work we explore the feasibility for this problem of a technique based on a robust multi-resolution opticalfow algorithm. The robustness is achieved adopting a Least Median of Squares paradigm. The algorithm has been tested on semi-synthetic data (i.e. real data that have been synthetically warped in order to have a reliable ground truth for the mo…

The exposure of the hybrid detector of the Pierre Auger Observatory

The Pierre Auger Observatory is a detector for ultra-high energy cosmic rays. It consists of a surface array to measure secondary particles at ground level and a fluorescence detector to measure the development of air showers in the atmosphere above the array. The ‘‘hybrid” detection mode combines the information from the two subsystems. We describe the determination of the hybrid exposure for events observed by the fluorescence telescopes in coincidence with at least one water-Cherenkov detector of the surface array. A detailed knowledge of the time dependence of the detection operations is crucial for an accurate evaluation of the exposure. We discuss the relevance of monitoring data coll…

MIS: Macro Icon System to generate macro algorithms for image analysis in parallel processing

Low Level Languages for the PAPIA Machine

The paper presents the low-level languages implemented up to date to program the PAPIA machine. The parallel assembly-level P-MAGRO package, the microcode level instruction set and a machine simulating environment are described.

A new heterogeneous and reconfigurable architecture for image analysis

In the paper a new architecture for image analysis: HERMIA (Heterogeneous and Reconfigurable Machine for Image Analysis) is presented. It has bt:en developed at the University of Palermo, inside the Progetto Finalizzato of the ltalian Council of Researches (CNR): Sistemi informatici e Calcolo Parallelo. The architecture of the HERMIA-machine is reconfigurable, moreover the integration of heterogeneous module, oriented to the solution of specific problems, allows to salve complex problems by search of optimal strategies. Signa! processing units allows the user to handle and integrate multi-sensors signals (from video, scanner, music recorder). Here the generai architecture, the hardware impl…

Silhouette encoding and synthesis using elliptic Fourier descriptors and applications to videoconferencing, Journal of Visual Language and Computing

This paper investigates the use of elliptic Fourier descriptors as a shape descriptor for encoding the silhouette of a person. Shape descriptors are here used for predicting the shape of silhouettes in missing frames within a sequence. This prediction scheme is applied to the case of generating in-between images in a low frame rate videoconferencing system, where the reconstructed silhouette is used as a binary mask for reducing the computational time for the frame reconstruction.

Segmentation and feature extraction in capillaroscopic videos

This contribution describes a method to select regions of interest as capillaries of the oral mucosa and to extract their main features useful for real diagnosis purposes. A discrete version of the wavelet transform has been adopted for segmenting the images coming from video sequences acquired by a prototype capillaroscopic, able to put in evidence the red blood flow. A set of proper characteristics is automatically computed for a correct evaluation of the peripheral microcirculation.

Automatic Individuation of Marine Biomass in Echo Images.

Scratch detection and removal from static images using simple statistics and genetic algorithms

This paper investigates the removal of line scratches from old movies and gives a twofold contribution. First, it presents simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, and it is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed with a conven…

A visual framework to support collaborative coding activities

In this paper, we present a framework named SIRENE, a Web-based visual programming environment, where teachers and students can collaboratively interact, using a flexible and versatile definition of visual programming code instead of pre-established rules. After the description of the architecture of the SIRENE framework, the preliminary results of a pilot trial with secondary school students will be presented; these results will lead to the final remarks and directions for further developments.

Finding essential features for tracking starfish in a video sequence

The paper introduces a software system for detecting and tracking starfish in an underwater video sequence. The target of such a system is to help biologists in giving an estimate of the number of starfish present in a particular area of the sea-bottom. The nature of the input images is characterised by a low signal/noise ratio and by the presence of noisy background represented by pebbles; this makes the detection a non-trivial task. The procedure we use is a chain of several steps that starts from the extraction of the area of interest and ends with a classifier and a tracker providing the necessary information for counting the starfish present in the scene. © 2003 IEEE.

Effects of low frequency electric fields on synaptic integration in hippocampal CA1 pyramidal neurons: implications for power line emissions

The possible cognitive effects of low frequency external electric fields, such as those generated by power lines, are poorly understood. Their functional consequences for mechanisms at the single neuron level are very difficult to study and identify experimentally, especially in vivo. The major open problem is that experimental investigations on humans have given inconsistent or contradictory results, making it difficult to estimate the possible effects of external low frequency electric fields on cognitive functions. Here we investigate this issue with a realistic model of hippocampal CA1 pyramidal neurons. The model suggests how and why external electric fields, with environmentally obser…

Clouds Simulation and Rendering

Clustering of low-correlated spatial gene expression patterns in the mouse brain in the Allen Brain Atlas

In this paper, clustering techniques are applied to spatial gene expression patterns with a low genomic correlation between the sagittal and coronal projections. The data analysed here are hosted on an available public DB named ABA (Allen Brain Atlas). The results are compared to those obtained by Bohland et al. on the complementary dataset (high correlation values). We prove that, by analysing a reduced dataset,hence reducing the computational burden, we get the same accuracy in highlighting different neuroanatomical region.

NeuronAlg: An Innovative Neuronal Computational Model for Immunofluorescence Image Segmentation

Background: Image analysis applications in digital pathology include various methods for segmenting regions of interest. Their identification is one of the most complex steps and therefore of great interest for the study of robust methods that do not necessarily rely on a machine learning (ML) approach. Method: A fully automatic and optimized segmentation process for different datasets is a prerequisite for classifying and diagnosing indirect immunofluorescence (IIF) raw data. This study describes a deterministic computational neuroscience approach for identifying cells and nuclei. It is very different from the conventional neural network approaches but has an equivalent quantitative and qu…

An Evolution of the Non-Parameter Harris Affine Corner Detector: A Distributed Approach

A parallel version of a new automatic Harris-based corner detector is presented. A scheduler to dynamically and homogeneously distribute high computational workload on heterogeneous parallel architectures such as Grid systems has been implemented to speedup the whole procedure. Experimental results show the robustness of the underlying scheduler, which can be easily exploited in various automatic image analysis systems.

Complex objects classified by morphological shape analysis and elliptical Fourier descriptors

This chapter deals with the classification of complex objects by morphological shape analysis and elliptical Fourier descriptors. An unsupervised method has been proposed to identify components with specific shapes by a simple edge detector and to classify them via the description of their contours. A particular application has been arranged in order to evaluate the goodness of this approach when discriminating between normal and pathological human megakaryocytes. Alterations in these cells can occur in many pathological processes and in such cases the pattern, size and shape of the cytoplasm and/or of the nucleus are extremely varied.

Wavelet analysis and neural network classifiers to detect mid-sagittal sections for nuchal translucency measurement

We propose a methodology to support the physician in the automatic identification of mid-sagittal sections of the fetus in ultrasound videos acquired during the first trimester of pregnancy. A good mid-sagittal section is a key requirement to make the correct measurement of nuchal translucency which is one of the main marker for screening of chromosomal defects such as trisomy 13, 18 and 21. NT measurement is beyond the scope of this article. The proposed methodology is mainly based on wavelet analysis and neural network classifiers to detect the jawbone and on radial symmetry analysis to detect the choroid plexus. Those steps allow to identify the frames which represent correct mid-sagitta…

A Wavelet approach to extract main features from indirect immunofluorescence images

A number of previous studies have shown that IIF image analysis requires complex and sometimes heterogeneous and diversified methods. Robust solutions can be proposed but they need to orchestrate several methods from low-level analysis up to more complex neural networks or SVM for data classification. The contribution intends to highlight the versatility of Wavelet Transform (WT) and their use in various levels of analysis for the classification of IIF images in order to develop a system capable of performing: image enhancement, ROI segmentation and object classification. Therefore, WT was adopted in the de-noise section, segmentation and classification. This analysis allows frequencies cha…

A Harris-based Region Detector on a Computational Grid

This paper introduces a new Harris-based feature detector algorithm, characterized by no parameters tuning to detect region of interest. Preliminary results show that the proposed methodology returns good results with respect to standard detectors which need a set of parameters. An uncommon parallel implementation of the proposed algorithm is presented to support the high computational workload which is required to avoid the approximation of the results. Our parallel approach differs from the conventional one because an internal scheduler, based on the expected running time, is used to balance the data distribution on a client-server model. The aim of this paper is also to underline the adv…

Morphological Analysis Combined with a Machine Learning Approach to Detect Utrasound Median Sagittal Sections for the Nuchal Translucency Measurement

The screening of chromosomal defects, as trisomy 13, 18 and 21, can be obtained by the measurement of the nuchal translucency thickness scanning during the end of the first trimester of pregnancy. This contribution proposes an automatic methodology to detect mid-sagittal sections to identify the correct measurement of nuchal translucency. Wavelet analysis and neural network classifiers are the main strategies of the proposed methodology to detect the frontal components of the skull and the choroid plexus with the support of radial symmetry analysis. Real clinical ultrasound images were adopted to measure the performance and the robustness of the methodology, thus it can be highlighted an er…

Experiments with an adaptive Bayesian restoration method

Abstract This paper describes a Bayesian restoration method applied to two-dimensional measured images, whose detector response function is not completely known. The response function is assumed Gaussian with standard deviation depending on the estimate of the local density of the image. The convex hull of the K -nearest neighbours ( K NN) of each ‘on’ pixel is used to compute the local density. The method has been tested on ‘sparse’ images, with and without noise background.

On the structural connectivity of large-scale models of brain networks at cellular level

AbstractThe brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the …

Automatic detection and measurement of nuchal translucency.

In this paper we propose a new methodology to support the physician both to identify automatically the nuchal region and to obtain a correct thickness measurement of the nuchal translucency. The thickness of the nuchal translucency is one of the main markers for screening of chromosomal defects such as trisomy 13, 18 and 21. Its measurement is performed during ultrasound scanning in the first trimester of pregnancy. The proposed methodology is mainly based on wavelet and multi resolution analysis. The performance of our method was analysed on 382 random frames, representing mid-sagittal sections, uniformly extracted from real clinical ultrasound videos of 12 patients. According to the groun…

Removal of streaking artefact in the images of the Pierre Auger Observatory infra-red cameras

In this paper the problem of removing concentric semi-circular stripe artefacts induced by the operating hardware of the infra red cameras of the Pierre Auger Observatory, is tackled. The method builds on top of a recent algorithm for the removal of artefacts, which presents a robust filter, obtained as a combination of Wavelet and Fourier analysis, capable of eliminating horizontal and vertical stripes in images, while trying to preserve structural features and quantitative values of the image. The method requires several parameters which have been tuned by an exhaustive test on a large set of images. The results show that the method is capable to satisfactorily remove the stripe artefacts.

Trigger and aperture of the surface detector array of the Pierre Auger Observatory

The surface detector array of the Pierre Auger Observatory consists of 1600 water-Cherenkov detectors, for the study of extensive airshowers (EAS) generated by ultra-high-energy cosmic rays. We describe the trigger hierarchy, from the identification of candidates howers at the level of a single detector, amongst a large background (mainly random single cosmic ray muons), up to the selection of real events and the rejection of random coincidences. Such trigger makes the surface detector array fully efficient for the detection of EAS with energy above 3 x 1018 eV, for all zenith angles between 03 and 603, independently of the position of the impact point and of the mass of the primary particl…

PDB: A pictorial database oriented to data analysis

The paper describes a new pictorial database oriented to image analysis, implemented inside the MIDAS data analysis system. Pictorial databases need expressive data structures in order to represent a wide class of information from the numerical to the visual. The model of the database is relational; however, a full normalization is not achievable, owing to the complexity of the visual information. The paper reports the general design and notes on the software implementation. Preliminary experiments show the performance of the pictorial database. Copyright © 1993 John Wiley & Sons, Ltd

Distributed Systems for Fusion of Visual Information

A Fast Multiresolution Approach Useful for Retinal Image Segmentation

Retinal diseases such as retinopathy of prematurity (ROP), diabetic and hypertensive retinopathy present several deformities of fundus oculi which can be analyzed both during screening and monitoring such as the increase of tortuosity, lesions of tissues, exudates and hemorrhages. In particular, one of the first morphological changes of vessel structures is the increase of tortuosity. The aim of this work is the enhancement and the detection of the principal characteristics in retinal image by exploiting a non-supervised and automated methodology. With respect to the well-known image analysis through Gabor or Gaussian filters, our approach uses a filter bank that resembles the “à trous” wav…

A genetic algorithm for scratch removal in static images

This paper investigates the removal of line scratches from old moving pictures and gives a twofold contribution. First, it presents a simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, which is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed wit…

Dealing with reconstruction problems: two cases study

Reconstruction problems are always included in a computer vision system as one of the key step toward the recognition of a scene. There are hierarchies of reconstruction that go from pixels to regions in the lower level, and from patches to objects in higher steps. The success of the reconstruction phase de-pends on several factors: the selection of "suitable" features, the matching function, the linking strategy. I this paper we show some of problems and solutions in two different contexts: the 3D reconstruction from cloud of points representing fragments of archeological finding, and the mosaicing from sea bed video frames. Preliminary results show that in both cases the accuracy is satis…

Automatic detection and classification of retinal vascular landmarks

The main contribution of this paper is introducing a method to distinguish between different landmarks of the retina: bifurcations and crossings. The methodology may help in differentiating between arteries and veins and is useful in identifying diseases and other special pathologies, too. The method does not need any special skills, thus it can be assimilated to an automatic way for pinpointing landmarks; moreover it gives good responses for very small vessels. A skeletonized representation, taken out from the segmented binary image (obtained through a preprocessing step), is used to identify pixels with three or more neighbors. Then, the junction points are classified into bifurcations or…

Dissimilarity Measures for the Identification of Earthquake Focal Mechanisms

This work presents a study about dissimilarity measures for seismic signals, and their relation to clustering in the particular problem of the identification of earthquake focal mechanisms, i.e. the physical phenomena which have generated an earthquake. Starting from the assumption that waveform similarity implies similarity in the focal parameters, important details about them can be determined by studying waveforms related to the wave field produced by earthquakes and recorded by a seismic network. Focal mechanisms identification is currently investigated by clustering of seismic events, using mainly cross-correlation dissimilarity in conjunction with hierarchical clustering algorithm. By…

Accurate estimation of retinal vessel width using bagged decision trees and an extended multiresolution Hermite model.

We present an algorithm estimating the width of retinal vessels in fundus camera images. The algorithm uses a novel parametric surface model of the cross-sectional intensities of vessels, and ensembles of bagged decision trees to estimate the local width from the parameters of the best-fit surface. We report comparative tests with REVIEW, currently the public database of reference for retinal width estimation, containing 16 images with 193 annotated vessel segments and 5066 profile points annotated manually by three independent experts. Comparative tests are reported also with our own set of 378 vessel widths selected sparsely in 38 images from the Tayside Scotland diabetic retinopathy scre…

noRANSAC for fundamental matrix estimation

The estimation of the fundamental matrix from a set of corresponding points is a relevant topic in epipolar stereo geometry [10]. Due to the high amount of outliers between the matches, RANSAC-based approaches [7, 13, 29] have been used to obtain the fundamental matrix. In this paper two new contributes are presented: a new normalized epipolar error measure which takes into account the shape of the features used as matches [17] and a new strategy to compare fundamental matrices. The proposed error measure gives good results and it does not depend on the image scale. Moreover, the new evaluation strategy describes a valid tool to compare diffe rent RANSAC-based methods because it does not re…

Filter Bank: a Directional Approach for Retinal Vessel Segmentation

It is well known that retinal diseases are sometimes identified by tortuosity of the vessels, presence of exudates and hemorrhages while lesions of tissues are associated to diabetic retinopathy, retinopathy of prematurity and more general cerebrovascular problems. One of the main issues in this research field is detecting small curvilinear structures, thus the aim of this contribution is to introduce a non-supervised and automated methodology to detect features such as curvilinear structures in retinal images. The core of the proposed methodology consists in using an approach that resembles the “a trous” wavelet algorithm. With respect to the standard Gabor analysis our methodology is base…