Search results for "image processing"

Extending CSG with projections: Towards formally certified geometric modeling

2015

We extend traditional Constructive Solid Geometry (CSG) trees to support the projection operator. Existing algorithms in the literature prove various topological properties of CSG sets. Our extension readily allows these algorithms to work on a greater variety of sets, in particular parametric sets, which are extensively used in CAD/CAM systems. Constructive Solid Geometry allows for algebraic representation which makes it easy for certification tools to apply. A geometric primitive may be defined in terms of a characteristic function, which can be seen as the zero-set of a corresponding system along with inequality constraints. To handle projections, we exploit the Disjunctive Normal Form,…

Interpreting Heterogeneous Geospatial Data Using Semantic Web Technologies

2016

International audience; The paper presents work on implementation of semantic technologies within a geospatial environment to provide a common base for further semantic interpretation. The work adds on the current works in similar areas where priorities are more on spatial data integration. We assert that having a common unified semantic view on heterogeneous datasets provides a dimension that allows us to extend beyond conventional concepts of searchability, reusability, composability and interoperability of digital geospatial data. It provides contextual understanding on geodata that will enhance effective interpretations through possible reasoning capabilities. We highlight this through …

Maximum likelihood difference scaling of image quality in compression-degraded images.

2007

International audience; Lossy image compression techniques allow arbitrarily high compression rates but at the price of poor image quality. We applied maximum likelihood difference scaling to evaluate image quality of nine images, each compressed via vector quantization to ten different levels, within two different color spaces, RGB and CIE 1976 L(*)a(*)b(*). In L(*)a(*)b(*) space, images could be compressed on average by 32% more than in RGB space, with little additional loss in quality. Further compression led to marked perceptual changes. Our approach permits a rapid, direct measurement of the consequences of image compression for human observers.

A structural representation of the customer's behavior for the characterization of the indecisiveness class

2014

National audience; no abstract

Procédé et dispositif de détermination de paramètres représentatifs d'une activité cardiovasculaire

2015

Ontology and protocol secure for SCADA: Int. J. of Metadata, Semantics and Ontologies, 2014 Vol.9, No.2, pp.114 - 127

2014

International audience; In this work, we present a semantic cyber security system and we study its semantic intelligent systems vulnerabilities, focusing on the semantic attacks. For resolving semantic problems we propose a security global solution for the new generation of SCADA systems. The proposed solution aims at protecting critical semantic SCADA processes from the effects of major failures and semantic vulnerabilities in the modern IT-SCADA network. We used a security block in the global network access point, security protocols deployed in different network (OSI) levels and security ontologies deployed in security devices. We used our mixed coordinates (ECC) cryptography solution, th…

Automatic classification of tissues using T1 and T2 relaxation times from prostate MRI: a step toward generation of PET/MR attenuation map

2015

This paper presents a new methodology providing the first step towards generating attenuation maps for PET/MR systems based solely on MR information. The new method segments and classifies the attenuation-differing regions of the patient's pelvis based on acquired T 1 - and T 2 -weighted MR data sets and anatomical-based knowledge by computing the tissue specific T 1 and T 2 relaxation times, using a robust implementation of the weighted fuzzy C-means algorithm and applying a novel process to detect bones. We have demonstrated the feasibility of this approach by correctly segmenting and classifying six differing regions of structural and anatomical importance: fat, muscle, prostate, air, ba…

Cardiac motion tracking using a deformable 2D-mesh modeling

2001

International audience; Abstract: The work reported here deals with movement tracking in sequences of medical images in order to quantify the general movements and deformations of the heart For this purpose, we partition the first image into triangular patches in order that each object of the image corresponds to a set of triangles. Then, the nodes of the mesh are tracked across the image sequence giving a mesh which warps with the images. The method is applied to cardiac image sequences where the study of the deformation of the triangles is applied to the determination of the movement of the ventricles

A Supervised Learning Framework for Automatic Prostate Segmentation in Trans Rectal Ultrasound Images

2012

International audience; Heterogeneous intensity distribution inside the prostate gland, significant variations in prostate shape, size, inter dataset contrast variations, and imaging artifacts like shadow regions and speckle in Trans Rectal Ultrasound (TRUS) images challenge computer aided automatic or semi-automatic segmentation of the prostate. In this paper, we propose a supervised learning schema based on random forest for automatic initialization and propagation of statistical shape and appearance model. Parametric representation of the statistical model of shape and appearance is derived from principal component analysis (PCA) of the probability distribution inside the prostate and PC…

Multiple Mean Models of Statistical Shape and Probability Priors for Automatic Prostate Segmentation

2011

International audience; Low contrast of the prostate gland, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow regions, speckle and significant variations in prostate shape, size and in- ter dataset contrast in Trans Rectal Ultrasound (TRUS) images challenge computer aided automatic or semi-automatic segmentation of the prostate. In this paper, we propose a probabilistic framework for automatic initialization and propagation of multiple mean parametric models derived from principal component analysis of shape and posterior probability information of the prostate region to segment the prostate. Unlike traditional statistical models of shape and int…