Search results for " images"
showing 10 items of 202 documents
Destructuration of typical Sicilian calcarenites
2010
The paper discusses some interesting features of Sicilian fine grain calcarenites. Uniaxial, triaxial, oedometer and isotropic compression tests were undertaken on intact specimens of two types of calcarenite in order to investigate their mechanical characteristics. It was found that the strength and deformability is significantly influenced by the structure (fabric and bonding) and by the destructuration processes. A better understanding of fracture development behavior is gained through a combination of acoustic emission and photographic monitoring on non-homogeneous samples with natural pre-existing heterogeneities due to cementation or to density. The results show that the destructurati…
Rural futures in developed economies: The case of Finland
2015
Abstract This study presents four possible images of rural futures in Finland: decentralized bio-economy, colonial countryside, museum countryside and rural business islets. They are distilled through literature reviews, futures workshops and futures tables. Alternative specifications of structures, contents and agencies result in highly divergent states of key dimensions and, consequently, divergent rural futures. This diversity challenges the conventional public wisdom or intellectual monoculture that considers decay as the only future for rural areas. Key challenges in crafting plausible but divergent futures images are finding an appropriate level of abstraction or “flight altitude”, es…
Fusion of multimodal data by combining the uncertainty and perception models
2019
The general idea is to use together heterogeneous multiple information on the same problem tainted by imperfections and coming from several sources in order to improve the knowledge of a given situation. Appropriate visualization of the images to aid in decision making using the perceptual information carried by the salience maps.
A Combined Fuzzy and Probabilistic Data Descriptor for Distributed CBIR
2009
With the wide diffusion of digital image acquisition devices, the cost of managing hundreds of digital images is quickly increasing. Currently, the main way to search digital image libraries is by keywords given by the user. However, users usually add ambiguos keywords for large set of images. A content-based system intended to automatically find a query image, or similar images, within the whole collection is needed. In our work we address the scenario where medical image collections, which nowadays are rapidly expanding in quantity and heterogeneity, are shared in a distributed system to support diagnostic and preventive medicine. Our goal is to produce an efficient content-based descript…
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 …
FCA-Net: Adversarial Learning for Skin Lesion Segmentation Based on Multi-Scale Features and Factorized Channel Attention
2019
International audience; Skin lesion segmentation in dermoscopic images is still a challenge due to the low contrast and fuzzy boundaries of lesions. Moreover, lesions have high similarity with the healthy regions in terms of appearance. In this paper, we propose an accurate skin lesion segmentation model based on a modified conditional generative adversarial network (cGAN). We introduce a new block in the encoder of cGAN called factorized channel attention (FCA), which exploits both channel attention mechanism and residual 1-D kernel factorized convolution. The channel attention mechanism increases the discriminability between the lesion and non-lesion features by taking feature channel int…
Relative risk estimation of dengue disease at small spatial scale
2017
Abstract Background Dengue is a high incidence arboviral disease in tropical countries around the world. Colombia is an endemic country due to the favourable environmental conditions for vector survival and spread. Dengue surveillance in Colombia is based in passive notification of cases, supporting monitoring, prediction, risk factor identification and intervention measures. Even though the surveillance network works adequately, disease mapping techniques currently developed and employed for many health problems are not widely applied. We select the Colombian city of Bucaramanga to apply Bayesian areal disease mapping models, testing the challenges and difficulties of the approach. Methods…
The Study of Dynamic Objects Identification Algorithms Based on Anisotropic Properties of Generalized Amplitude-Phase Images
2018
The article presents some results of dynamical objects identification technology based on coincidence matrixes of templates and tested objects’ amplitude-phase images (APIm) calculated with discrete Hilbert transforms (DHT). DHT algorithms are modeled on basis of isotropic (HTI), anisotropic (HTA), generalized transforms – AP-analysis (APA) and the difference (residual) relative shifted phase (DRSP-) images to calculate the APIm. The identified objects are recognized as members of classes modeled with 3D templates – images of different types airplanes rotated in space. The dynamic anisotropic properties of APIm causes the increasing of sensitivity to circular angle rotation and make possibl…
A Specialized Architecture for Color Image Edge Detection Based on Clifford Algebra
2013
Edge detection of color images is usually performed by applying the traditional techniques for gray-scale images to the three color channels separately. However, human visual perception does not differentiate colors and processes the image as a whole. Recently, new methods have been proposed that treat RGB color triples as vectors and color images as vector fields. In these approaches, edge detection is obtained extending the classical pattern matching and convolution techniques to vector fields. This paper proposes a hardware implementation of an edge detection method for color images that exploits the definition of geometric product of vectors given in the Clifford algebra framework to ex…
Improving point matching on multimodal images using distance and orientation automatic filtering
2016
International audience; Speed Up Robust Features SURF is one of the most popular and efficient methods used for image registration task. In order to achieve a correct registration, a good matching of feature point is required. However in the case of multimodal images, the high and non-linear intensity changes between different modalities led to many outliers (mismatching of detected points) and consequently a fail in the registration. Therefore, in this paper we introduce an efficient method devoted to the detection and removal of such outlier. It's based on an automatic filtering of outliers on both distance and orientation between features points. We tested our proposed method on a set of…