Search results for " Pattern Recognition"
showing 10 items of 1050 documents
Different averages of a fuzzy set with an application to vessel segmentation
2005
Image segmentation is a major problem in image processing, particularly in medical image analysis. A great number of segmentation procedures produce intermediate gray-scale images that can be understood as fuzzy sets. Additionally, some segmentation procedures tend to leave free tuning parameters (very influential in the final binary image) for the user. These different binary images can be easily aggregated (into a fuzzy set) by making use of fuzzy set theory. In any case, a single binary image is required so our interest is to associate a crisp set to a given fuzzy set in an intelligent and unsupervised manner. The main idea of this paper is to define the averages of a given fuzzy set by …
Unsupervised tissue classification of brain MR images for voxel-based morphometry analysis
2016
In this article, a fully unsupervised method for brain tissue segmentation of T1-weighted MRI 3D volumes is proposed. The method uses the Fuzzy C-Means (FCM) clustering algorithm and a Fully Connected Cascade Neural Network (FCCNN) classifier. Traditional manual segmentation methods require neuro-radiological expertise and significant time while semiautomatic methods depend on parameter's setup and trial-and-error methodologies that may lead to high intraoperator/interoperator variability. The proposed method selects the most useful MRI data according to FCM fuzziness values and trains the FCCNN to learn to classify brain’ tissues into White Matter, Gray Matter, and Cerebro-Spinal Fluid in …
Keypoint descriptor matching with context-based orientation estimation
2014
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…
Using skeleton and Hough transform variant to correct skew in historical documents
2020
International audience; As a main part of several document analysis systems, Skew estimation represents one of the major research challenges, particularly in case of historical documents exploration. In this paper, we propose an original skew angle detection and correction technique. Morphological Skeleton is introduced to considerably diminish the amount of data by eliminating the redundant pixels and preserving only the central curves of the image components. Next, the proposed method uses Progressive Probabilistic Hough Transform (PPHT) to find image lines. At the end, a specific procedure is applied in order to measure the global skew angle of the document image from these identified li…
An efficient method for fully automatic 3D digitization of unknown objects
2013
Our goal is to develop a complete and automatic scanning strategy with minimum prior information about the object shape. We aim to establish a methodology for the automation of the 3D digitization process. The paper presents a novel approach to determine the Next Best View (NBV) for an efficient reconstruction of highly accurate 3D models. Our method is based on the classification of the acquired surfaces into Well Visible and Barely Visible combined with a best view selection algorithm based on mean shift, which avoids unreachable positions. Our approach is applicable to all kinds of range sensors. To prove the efficiency and the robustness of our method, test objects are first scanned man…
Irregular motion recovery in fluorescein angiograms
1997
Abstract Fluorescein angiography is a common procedure in ophthalmic practice, mainly to evaluate vascular retinopathies and choroidopathies from sequences of ocular fundus images. In order to compare the images, a reliable overlying is essential. This paper proposes some methods for the recovery of irregular motion in fluorescein angiograms (FA). The overlying is done by a three step procedure: detection of relevant points, matching points from different images and estimation of the assumed linear geometric transformation. A stochastic model (closely related to the general linear model) allows to fuse the second and third steps. Two different estimators of the geometric transformation are …
Order statistics-based parametric classification for multi-dimensional distributions
2013
Traditionally, in the field of Pattern Recognition (PR), the moments of the class-conditional densities of the respective classes have been used to perform classification. However, the use of phenomena that utilized the properties of the Order Statistics (OS) were not reported. Recently, in [10,8], we proposed a new paradigm named CMOS, Classification by the Moments of Order Statistics, which specifically used these quantifiers. It is fascinating that CMOS is essentially ''anti''-Bayesian in its nature because the classification is performed in a counter-intuitive manner, i.e., by comparing the testing sample to a few samples distant from the mean, as opposed to the Bayesian approach in whi…
Estimation of Purkinje trees from electro-anatomical mapping of the left ventricle using minimal cost geodesics
2015
The electrical activation of the heart is a complex physiological process that is essential for the understanding of several cardiac dysfunctions, such as ventricular tachycardia (VT). Nowadays, patient-specific activation times on ventricular chambers can be estimated from electro-anatomical maps, providing crucial information to clinicians for guiding cardiac radio-frequency ablation treatment. However, some relevant electrical pathways such as those of the Purkinje system are very difficult to interpret from these maps due to sparsity of data and the limited spatial resolution of the system. We present here a novel method to estimate these fast electrical pathways from the local activati…
Gesture recognition using low-cost devices: Techniques, applications, perspectives
2016
Negli ultimi anni abbiamo assistito ad una grande diffusione dei cosiddetti “Kinect-like devices”, ovvero dispositivi basati su un insieme di sensori a basso costo, che consentono di ottenere un’immagine di profondità della scena ripresa. L’alta accessibilità di questi dispositivi, principalmente in termini di costi, ne ha facilitato la diffusione nell’ambito del riconoscimento dei gesti in numerose applicazioni, sia commerciali che di ricerca. In questo articolo saranno inizialmente illustrati i principi generali su cui si fondano le principali tecniche utilizzate per riconoscere i gesti, sfruttando i dati ottenibili dai dispositivi “Kinect-like”. Successivamente, saranno presentati alcuni…
Conjugate Gradient Method for Brain Magnetic Resonance Images Segmentation
2018
Part 8: Pattern Recognition and Image Processing; International audience; Image segmentation is the process of partitioning the image into regions of interest in order to provide a meaningful representation of information. Nowadays, segmentation has become a necessity in many practical medical imaging methods as locating tumors and diseases. Hidden Markov Random Field model is one of several techniques used in image segmentation. It provides an elegant way to model the segmentation process. This modeling leads to the minimization of an objective function. Conjugate Gradient algorithm (CG) is one of the best known optimization techniques. This paper proposes the use of the nonlinear Conjugat…