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- W2364862560 abstract "For enhancing the intelligence level of tea processing,a method for discriminating images of four different kinds of green tea was put forward based on texture analysis.First,green tea images were obtained from three charged coupled device camera,which could simultaneously obtain three images from green,red and near-infrared channels.The statistical information derived from the combination of gray level co-occurrence matrix(GLCM) and texture filtering was used to describe the textural features of image.The results of unsupervised cluster analysis indicated that the combined textural features were more optimal than those from GLCM.Then ten optimized texture parameters were selected as input for least squares support vector machine(LS-SVM) classifier.This classifier got high recognition rate(94.4%) for 126 samples in calibration set,and same excellent performance was obtained for discrimination of 64 unknown samples in prediction set with 93.8%.The result indicated that it is feasible to discriminate tea images of different kinds of green tea based on combined textural feature extraction and LS-SVM classifier." @default.
- W2364862560 created "2016-06-24" @default.
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- W2364862560 date "2008-01-01" @default.
- W2364862560 modified "2023-09-26" @default.
- W2364862560 title "Texture discrimination of different kinds of green tea based on multi-spectral imaging technique" @default.
- W2364862560 hasPublicationYear "2008" @default.
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