Texture information in run-length matrices

Authors:
Xiaoou Tang
Affiliations:
Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin
Venue:
IEEE Transactions on Image Processing
Year:
1998

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Abstract

We use a multilevel dominant eigenvector estimation algorithm to develop a new run-length texture feature extraction algorithm that preserves much of the texture information in run-length matrices and significantly improves image classification accuracy over traditional run-length techniques. The advantage of this approach is demonstrated experimentally by the classification of two texture data sets. Comparisons with other methods demonstrate that the run-length matrices contain great discriminatory information and that a good method of extracting such information is of paramount importance to successful classification