Multispectral segmentation and textural feature extraction
Brigitte Hoeltzener-Douarin, Cyril Maurette, Patrick J. Bonnin, Edwige E. Pissaloux · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
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.