16 June 1995 Multispectral segmentation and textural feature extraction
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This paper focuses on the design of segmentation based on textural features extraction. This is an example of a transposition between biological and visual phenomena used in order to characterize natural image understanding. This is also an illustration of a more general appraoch to IP knowledge representation based on a methodology dedicated to the formalization of concrete and abstract models for image processing applications. It proposes an ontology which includes conceptual specifications borrowed from mathematics and physical and biological axiomatics which give concrete and more natural sense to our IP models. This provides a set of elementary definitions which can be used for the expression of concrete models such as image segmentation or pattern detection. In the case of texture we would like to formalize grey level behavior through processings based on multiple window analysis (spectral and morphological criteria: grey level and compacity). In this framework, the evolutionary models studied are issued from biological modeling of migration and mutation. Our illustration is relevant to multispectral segmentation where the homogeneity criterion has been modelized by a grey level evolution function based on exponentiation.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Brigitte Hoeltzener-Douarin, Cyril Maurette, Patrick J. Bonnin, and Edwige E. Pissaloux "Multispectral segmentation and textural feature extraction", Proc. SPIE 2488, Visual Information Processing IV, (16 June 1995); doi: 10.1117/12.212008; https://doi.org/10.1117/12.212008


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