@inproceedings{096d60ac58b44fa281fcafc26ce531b0,
title = "Combined geometric-texture image classification",
abstract = "In this paper, we propose a framework to carry out supervised classification of images containing both textured and non textured areas. Our approach is based on active contours. Using a decomposition algorithm inspired by the recent work of Y. Meyer, we can get two channels from the original image to classify: one containing the geometrical information, and the other the texture. Using the logic framework by Chan and Sandberg, we can then combine the information from both channels in a user definable way. Thus, we design a classification algorithm in which the different classes are characterized both from geometrical and textured features. Moreover, the user can choose different ways to combine information.",
keywords = "Active contour, Classification, Decomposition, Geometrical image, Level-set, Logic model, PDE, Texture, Wavelets",
author = "Aujol, {Jean Fran{\c c}ois} and Tony Chan",
year = "2005",
doi = "10.1007/11567646_14",
language = "English (US)",
isbn = "3540293485",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "161--172",
booktitle = "Variational, Geometric, and Level Set Methods in Computer Vision - Third International Workshop, VLSM 2005, Proceedings",
note = "3rd International Workshop on Variational, Geometric, and Level Set Methods in Computer Vision, VLSM 2005 ; Conference date: 16-10-2005 Through 16-10-2005",
}