This paper presents a new image segmentation approach based on distributed agents. In this approach, the segmentation is performed trough a simulation of the hybrid architecture of P2P networks by introducing the concept of “super agent”. Each super agent corresponds to an area of the image. The segmentation process within that zone is done by ordinary agents supervised by the super agent. Segm...

Image segmentation is the process of partitioning or divisioning of an image into homogeneous and self consistent region which doesn’t overlap with each other.The segmentation is based on color, texture, motion, depth, gray level etc. The level of detail in which the partitioning is carried out is depend on the application. Several general-purpose algorithms and techniques have been developed f...

Almost all document analysis approaches need to perform a global analysis of the page orientation as a separate process at an early stage. It would be preferable to estimate the orientation locally after page segmentation and classification, when more knowledge about the different regions is available. In this paper, a novel local skew estimation method is presented that takes advantage of the ...

This paper presents a new method for unsupervised urban area extraction from SAR imagery. The image segmentation method combines variogram texture feature extraction with OTSU threshold segmentation method, to obtain the result as good as traditional classical algorithm and have much higher computational efficiency. TerraSAR-X image is used to validate the proposed method, and experimental resu...

In this contribution we introduce a new method for global segmentation of color documents with a structure based on text frames and pictures. It is based on an extensive analysis of the expected shape of clusters in RGB-color space. The method provides an improved segmentation, and gives a proper basis for indexing and layout analysis. Results are very promising. keywords: color documents, docu...

Internet search is one of the most important applications of the Web. One shortcoming of existing search techniques is that they do not give due consideration to the micro-structures of a Web page. A Web page is often populated with a number of small information units, which we call micro information units (MIU). Each unit focuses on a specific topic and occupies a specific area of the page. Du...

In this paper, WC show how to extract reliable informations about the shape of 3D objects, obtained from volume medical images. We present an optimal region-growing algorithm, that makes use of the differential characteristics of the object surface, and achieves a stable segmentation into a set of patches of quadratic surfaces. We show how this segmentation can be used to recognize and locate a...

A new Markovianity approach is introduced in this paper. This approach reduces the response time of classic Markov Random Fields approach. First, one region is determinated by a clustering technique. Then, this region is excluded from the study. The remaining pixel form the study zone and they are selected for a Markovianity segmentation task. With Selective Markovianity approach, segmentation ...

Tumour is an uncontrolled growth of tissues in any part of the body. Tumours are of different types and characteristics and have different treatments. Detection of tumour in the earlier stages makes the treatment easier. Here a brief review of different segmentation methods used for detection of tumour from Magnetic Resonance Imaging (MRI) of brain has been discussed. Finally we propose an auto...