Issue No. 01 - January (1988 vol. 10)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.3870
<p>Two standard approaches for texture analysis make use of numerical features of the second-order gray-level statistics, and on first-order statistics of gray-level differences, respectively. Feature sets of these types, all designed analogously, were used to analyze four sets of carpet samples exposed to different degrees of wear. It was found that some of the features extracted from the spatial gray-level-dependence matrix, neighboring gray-level-dependence matrix, gray-level difference method, and the gray-level run-length method allowed discrimination of degrees of wear in wool carpet. The methods developed could be of use in quality control.</p>
computer vision; feature extraction; carpet wear assessment; texture analysis; second-order gray-level statistics; first-order statistics; gray-level differences; spatial gray-level-dependence matrix; neighboring gray-level-dependence matrix; gray-level run-length method; wool carpet; quality control; computer vision; computerised pattern recognition; textile industry; wear
R. Hodgson, E. Wood and L. Siew, "Texture Measures for Carpet Wear Assessment," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 10, no. , pp. 92-105, 1988.