Pomelo’s Quality Classification Based on Combination of Color Information and Gabor Filter
Vietnam is a country with strength in fruit trees, including many fruits well-known to the world, such as pomelo, dragon fruit, star apple, mango, durian, rambutan, longan, litchi and watermelon. However, the competitiveness and export of these fruits are low and incommensurate with the existing potential. To solve this problem, Vietnam is studying sustainable directions by investing in machinery for automation process to meet international standards. In this paper, we introduce an effective method for detecting surface defects of the pomelo automatically based on the combination of color information and Gabor filter. Our approach begins by representing the input image in HSV color space, computing the compactness based on the H channel, extracting texture parameters and using the K-nearest neighbor algorithm for quality classification. The proposed approach has been tested with high accuracy and is promising.
KeywordsInput Image Color Space Surface Defect Gabor Filter Gabor Wavelet
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