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- W191944900 abstract "In allusion to the problem that the existing fruit recognition methods either require large samples or can only identify single feature, the recognition method, based on the grey weighting correlation and fuzzy membership, has been proposed in this paper. This method extracts the color, size and shape features within the region of interest (ROI), for the color feature, according to the grey weighting correlation algorithm, respectively calculates its grey weighing correlation with the reference fruits, and for the size and shape features, according to the fuzzy membership functions of the reference fruits, respectively calculates the degrees of membership with the reference fruits. Finally summing the grey weighting correlation and fuzzy membership degree and averaging them up, extracting its maximum value and comparing it with the recognition threshold to get the recognition results, among which the recognition threshold is given through the experimental statistical analysis. This method effectively avoids affecting the image feature information because of image quality change during the image preprocessing, and it can completely eliminate the influence of background noise, which immensely improves the fruit recognition accuracy." @default.
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- W191944900 date "2012-04-06" @default.
- W191944900 modified "2023-09-24" @default.
- W191944900 title "The Globular Fruit Recognition Method Based on Grey Weighting Correlation and Fuzzy Membership" @default.
- W191944900 doi "https://doi.org/10.1109/iceice.2012.380" @default.
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