DocumentCode :
3368065
Title :
A new textured image segmentation algorithm by autoregressive modelling and multiscale block classification
Author :
Claude, I. ; Smolarz, A.
Author_Institution :
Univ. de Technol. de Troyes, France
Volume :
2
fYear :
1997
fDate :
14-17 Jul 1997
Firstpage :
586
Abstract :
Usually, we begin the analysis of an image by partitioning it into several homogeneous regions; this is the image segmentation. The homogeneity can be defined by many properties such as gray level intensity, color, texture, etc. In many cases, the texture is the only available information. Texture analysis, as a result, has received considerable attention for the last two decades. A large number of approaches for texture classification and segmentation have been suggested. Commonly, two types of approaches are distinguished, adapted respectively to macro- and microtextures, namely, the structural and statistical approaches. As far as the latter is concerned, we can cite probabilistic methods based on texture modelling, statistical methods which characterize an image in terms of numerical attributes or features and new tools like neural networks, wavelets, multiresolution and multiscale approaches, and fuzzy modelling. A few methods also come from signal processing and seem to be promising: bidimensional autoregressive modelling and, time-frequency and time-scale representations. We focus on stochastic approaches and, specifically, on texture modelling by bidimensional autoregressive models (2D-AR models). We describe the AR model; we propose our method for choosing an adapted neighbourhood and evaluation. Then, our segmentation algorithm is presented with the classification criterion and the contextual information. Finally, we present experimental results showing the influence of the context and demonstrating the improvements brought by the adapted models and the multiscale approach
Keywords :
image texture; 2D-AR models; adapted neighbourhood; bidimensional autoregressive modelling; color; contextual information; experimental results; gray level intensity; homogeneous image regions; image analysis; multiscale approach; multiscale block classification; probabilistic methods; signal processing; statistical approach; statistical methods; stochastic approaches; texture analysis; texture classification; texture modelling; texture segmentation; textured image segmentation algorithm;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Image Processing and Its Applications, 1997., Sixth International Conference on
Conference_Location :
Dublin
ISSN :
0537-9989
Print_ISBN :
0-85296-692-X
Type :
conf
DOI :
10.1049/cp:19970959
Filename :
615593
Link To Document :
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