Search results for " categorization"
showing 10 items of 54 documents
Chaotic multiagent system approach for MRF-based image segmentation
2005
In this paper, we propose a new chaotic approach for image segmentation based on multiagent system (MAS). We consider a set of segmentation agents organized around a coordinator agent. Each segmentation agent performs iterated conditional modes (ICM) starting from its own initial image created using a chaotic mapping. The coordinator agent diversifies the initial images using a crossover and a chaotic mutation operators. The efficiency of our chaotic MAS approach is shown through some experimental results.
Hidden Markov Random Fields and Direct Search Methods for Medical Image Segmentation
2016
The goal of image segmentation is to simplify the representation of an image to items meaningful and easier to analyze. Medical image segmentation is one of the fundamental problems in image processing field. It aims to provide a crucial decision support to physicians. There is no one way to perform the segmentation. There are several methods based on HMRF. Hidden Markov Random Fields (HMRF) constitute an elegant way to model the problem of segmentation. This modelling leads to the minimization of an energy function. In this paper we investigate direct search methods that are Nelder-Mead and Torczon methods to solve this optimization problem. The quality of segmentation is evaluated on grou…
Image Segmentation based on Genetic Algorithms Combination
2005
The paper describes a new image segmentation algorithm called Combined Genetic segmentation which is based on a genetic algorithm. Here, the segmentation is considered as a clustering of pixels and a similarity function based on spatial and intensity pixel features is used. The proposed methodology starts from the assumption that an image segmentation problem can be treated as a Global Optimization Problem. The results of the image segmentations algorithm has been compared with recent existing techniques. Several experiments, performed on real images, show good performances of our approach compared to other existing methods.
A Coupled Schema of Probabilistic Atlas and Statistical Shape and Appearance Model for 3D Prostate Segmentation in MR Images
2012
International audience; A hybrid framework of probabilistic atlas and statistical shape and appearance model (SSAM) is proposed to achieve 3D prostate segmentation. An initial 3D segmentation of the prostate is obtained by registering the probabilistic atlas to the test dataset with deformable Demons registration. The initial results obtained are used to initialize multiple SSAMs corresponding to the apex, central and base regions of the prostate gland to incorporate local variabilities. Multiple mean parametric models of shape and appearance are derived from principal component analysis of prior shape and intensity information of the prostate from the training data. The parameters are then…
The role of sociales identities in the social representation of the fatigue in France and Syrie
2015
For a few years, many factors, such as the burden of training, are considered to be linked to the athletes’ difficulties to get used to training. The fatigue is one of the perceived problems by the athletes. Physiologically, the fatigue can be defined as “the decrease of a muscle’s capacity over time to exert force or power during a given exercise”. However, from the social point of view, the interpretation of fatigue is different and varies according to the social groups. This representation of the fatigue, specific to each group, should be considered as “a form of knowledge, socially developed and shared. In this doctoral thesis, we focus on the representation of fatigue in France and in …
A novel active contour model for unsupervised low-key image segmentation
2013
Published version of an article in the journal: Central European Journal of Engineering. Also available from the publisher at: http://dx.doi.org/10.2478/s13531-012-0050-0 Unsupervised image segmentation is greatly useful in many vision-based applications. In this paper, we aim at the unsupervised low-key image segmentation. In low-key images, dark tone dominates the background, and gray level distribution of the foreground is heterogeneous. They widely exist in the areas of space exploration, machine vision, medical imaging, etc. In our algorithm, a novel active contour model with the probability density function of gamma distribution is proposed. The flexible gamma distribution gives a bet…
Exemplarity measurement and estimation of the level of interjudge agreement for two categories of French red wines
2015
Abstract Exemplarity measurements of wines by at least 20 judges are used to estimate the degree of interjudge (dis)agreement and to tell wines apart into two contrasting extremes. Two sets of French red wines – Pinot noir from Burgundy and Cabernet franc from the Loire Valley – are studied separately but by the same approach. Short-listing criteria are used to collate 40 starting-price and middle-range wines for each set differing a priori in olfactory terms. Wine professionals assess their local wines first orthonasally and then, independently, by global evaluation. A pool of descriptive and inferential statistics indicates there is generally neither complete divergence nor real agreement…
An Image Segmentation Algorithm based on Community Detection
2016
International audience; With the recent advances in complex networks, image segmentation becomes one of the most appropriate application areas. In this context, we propose in this paper a new perspective of image segmentation by applying two efficient community detection algorithms. By considering regions as communities, these methods can give an over-segmented image that has many small regions. So, the proposed algorithms are improved to automatically merge those neighboring regions agglomerative to achieve the highest modularity/stability. To produce sizable regions and detect homogeneous communities, we use the combination of a feature based on the Histogram of Oriented Gradients of the …
Manufactured object sub-segmentation based on reflection motion estimation
2015
International audience; In computer vision, reflection is a long-standing problem, it covers image textures, makes original color difficult to recognize, complicates the understanding of the scene. Most of the time, it is considered as “noise”. Many methods are proposed in order to reduce or delete the reflection effects in the image, but generally, the performances are not quite satisfactory. While instead of working on “de-noising”, we propose a method to take advantage of moving reflections that can be used for different computer vision applications. For instance, the segmentation of reflective manufactured objects is presented in this paper. We focus on tracking reflection components an…
The co-construction of the identical positionings of teachers and pupils in physical education
2015
This doctoral work is interested in the identical positionings of the teachers and the pupils led by the relation that the social scene in Physical Education establishes between them. These positionings are approached by means of the theories bound to the social categorization and more precisely the theory of the social identity, the theory of the auto-categorization and the conception of the social partitions. If the social partitions establish a continuation of the first two theories, they also rest on their own theoretical foundation, based on social psychology of the language. The goal of the first work was to propose a review of certain principles of the social categorization. This pro…