Self-eigenroughness selection for texture recognition using genetic algorithms

Authors:
Jing-Wein Wang
Affiliations:
Institute of Photonics and Communications, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan, R.O.C.
Venue:
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Year:
2007

Citing 2
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Abstract

To test the effectiveness of Self-Eigenroughness, which is derived from performing principal component analysis (PCA) on each texture roughness individually, in texture recognition with respect to Eigenroughness, which is derived from performing PCA on all texture roughness; we present a novel fitness function with adaptive threshold to evaluate the performance of each subset of genetically selected eigenvectors. Comparatively studies suggest that the former is superior to the latter in terms of recognition accuracy and computation efficiency.