We propose a learning-based approach for automatic detection of fabric defects. Our
approach is based on a statistical representation of fabric patterns using the redundant …

In this paper, we develop a new framework for contourlet-based statistical modeling using
finite Mixtures of Generalized Gaussian distributions (MoGG). On the one hand, given the …

Segmentation of medical images is one of the fundamental problems in image processing
field. It aims to provide a crucial decision support to physicians. There are several methods …

We introduce a mixture of mixtures of bounded asymmetric generalized Gaussian and
uniform distributions. Based on this framework, we propose model-based classification and …

Résumé Dans le domaine de l'imagerie médicale, la segmentation des images est une
tâche cruciale, qui permet d'isoler dans l'image les objets significatifs sur lesquels doit porter …

In recent times, the rapid growth of data in various fields of life has created an immense
need for powerful tools to extract useful information from data. This has motivated …

The paper presents a method for estimating parameters of the mixture of Gaussian
distributions that can be used for constructing likelihood functions at automatic clustering of …

Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …

In this thesis, we deal with the foreground segmentation (FS) problem that is a key issue to
numerous computer vision applications such as document analysis, object recognition, and …

In this thesis, we deal with the foreground segmentation (FS) problem that is a key issue to
numerous computer vision applications such as document analysis, object recognition, and …