Texture classification using C-matrix and the fuzzy min-max neural network

Youn-Jen Chang; Hsiao-Rong Tyan; Hong-Yuan Mark Liao

doi:10.1117/12.186024

16 September 1994 Texture classification using C-matrix and the fuzzy min-max neural network

Youn-Jen Chang, Hsiao-Rong Tyan, Hong-Yuan Mark Liao

Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994) https://doi.org/10.1117/12.186024
Event: Visual Communications and Image Processing '94, 1994, Chicago, IL, United States

Abstract

In this paper, we propose a new texture classification method. Previously, for texture analysis and classification, the gray tone co-occurrence matrix was adopted most frequently. However, due to the complexity in its derivation process, it is not the best choice if the processing time is a major concern. In this work, we propose a more compact matrix called C-matrix to solve the above problem. The proposed C-matrix characterizes both qualitative and quantitative properties between each pixel and its neighbors in an image. Based on this matrix, a set of statistical features can be defined. These features are then fed into a trained fuzzy neural network for texture classification. Experimental results based on two ground surface images are reported to corroborate the proposed theory.

Citation Download Citation

Youn-Jen Chang, Hsiao-Rong Tyan, and Hong-Yuan Mark Liao "Texture classification using C-matrix and the fuzzy min-max neural network", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); https://doi.org/10.1117/12.186024

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