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Proceedings Paper

Texture classification using C-matrix and the fuzzy min-max neural network
Author(s): Youn-Jen Chang; Hsiao-Rong Tyan; Hong-Yuan Mark Liao
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Paper 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.

Paper Details

Date Published: 16 September 1994
PDF: 10 pages
Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.186024
Show Author Affiliations
Youn-Jen Chang, Chung Yuan Christian Univ. (Taiwan)
Hsiao-Rong Tyan, Chung Yuan Christian Univ. (Taiwan)
Hong-Yuan Mark Liao, Institute of Information Science (Taiwan)


Published in SPIE Proceedings Vol. 2308:
Visual Communications and Image Processing '94
Aggelos K. Katsaggelos, Editor(s)

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