Texture information in run-length matrices

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.

• Type: Journal
• Year: 1998
• Where: TIP
• Authors: Xiaoou Tang
• Keywords: Run-length, Run-length Matrices, TIP 1998, Traditional Run-length Techniques