Human Understandable Features for Segmentation of Solid Texture

Authors:
Ludovic Paulhac;Pascal Makris;Jean-Marc Gregoire;Jean-Yves Ramel
Affiliations:
Laboratoire Informatique (EA2101), Université François Rabelais Tours,;Laboratoire Informatique (EA2101), Université François Rabelais Tours,;UMR INSERM U930, CNRS ERL 3106, équipe 5, Université François Rabelais Tours,;Laboratoire Informatique (EA2101), Université François Rabelais Tours,
Venue:
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Year:
2009

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Abstract

The purpose of this paper is to present new texture descriptors dedicated to segmentation of solid textures. The proposed texture attributes are inspired by the human description of texture and allows a general description of texture. Moreover it is more convenient for a user to understand features signification particularly in a man-aided application. In comparison with psychological measurements for human subjects, our characteristics gave good correspondences in rank correlation of 12 different solid textures. Using these texture features, segmentation results obtained with the classical K-means method on solid textures and real three-dimensional ultrasound images of the skin are presented and discussed.