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Proceedings Paper

Gabor-wavelet decomposition and integrated PCA-FLD method for texture based defect classification
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Paper Abstract

In many hyperspectral applications, it is desirable to extract the texture features for pattern classification. Texture refers to replications, symmetry of certain patterns. In a set of hyperspectral images, the differences of image textures often imply changes in the physical and chemical properties on or underneath the surface. In this paper, we utilize Gabor wavelet based texture analysis method for textural pattern extraction, and combined with integrated PCA-FLD method for hyperspectral band selection in the application of classifying chilling damaged cucumbers from normal ones. The classification performances are compared and analyzed.

Paper Details

Date Published: 8 November 2005
PDF: 9 pages
Proc. SPIE 5996, Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, 59960V (8 November 2005); doi: 10.1117/12.631071
Show Author Affiliations
Xuemei Cheng, Univ. of Maryland, College Park (United States)
Yud-Ren Chen, USDA Instrumentation and Sensing Lab. (United States)
Tao Yang, Univ. of Maryland, College Park (United States)
Xin Chen, Univ. of Maryland, College Park (United States)


Published in SPIE Proceedings Vol. 5996:
Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

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