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Proceedings Paper

Multispectral segmentation and textural feature extraction
Author(s): Brigitte Hoeltzener-Douarin; Cyril Maurette; Patrick J. Bonnin; Edwige E. Pissaloux
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Paper Abstract

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.

Paper Details

Date Published: 16 June 1995
PDF: 12 pages
Proc. SPIE 2488, Visual Information Processing IV, (16 June 1995); doi: 10.1117/12.212008
Show Author Affiliations
Brigitte Hoeltzener-Douarin, ETCA/CREA/SP (France)
Cyril Maurette, ETCA/CREA/SP (France)
Patrick J. Bonnin, ETCA/CREA and Univ. Paris XIII (France)
Edwige E. Pissaloux, Univ. Paris XIII (France)


Published in SPIE Proceedings Vol. 2488:
Visual Information Processing IV
Friedrich O. Huck; Richard D. Juday, Editor(s)

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