8 November 2005 Gabor-wavelet decomposition and integrated PCA-FLD method for texture based defect classification
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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.
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Xuemei Cheng, Yud-Ren Chen, Tao Yang, Xin Chen, "Gabor-wavelet decomposition and integrated PCA-FLD method for texture based defect classification", 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; https://doi.org/10.1117/12.631071
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