Object Segmentation of Color Video Sequences
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
The Poisson equation for image texture modelling
Pattern Recognition Letters
Hierarchical multiple Markov chain model for unsupervised texture segmentation
IEEE Transactions on Image Processing
Entropy controlled gauss-markov random measure field models for early vision
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
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This paper presents an unsupervised texture segmentation algorithm based on feature extraction using multichannel Gabor filtering. It is shown that feature contrast, a criterion derived for Gabor filter parameter selection, is well suited for feature coordinate weighting in order to reduce the feature space dimension. The central idea of the proposed segmentation algorithm is to decompose the actual segmented image into disjunct areas called scrap images and use them after lowpass filtering as additional features for repeated k-means clustering and minimum distance classification. This yields a classification of texture regions with an improved degree of homogeneity while preserving precise texture boundaries