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- W2481632859 abstract "In order to research the diversity, unity and stability (DUS test) of different varieties of peanut, the method of image recognition is used. Images of 20 varieties of peanut are collected through scanner. Images of 100 peanut seeds' facade and two sides of each variety are collected, each image's characteristics of shape, color and texture totaling up to 50 are obtained which are recognized by an artificial neural net recognition model based on them. Each characteristic is tested with the model. It is showed that the maximum recognition rate of the different characteristics of 20 varieties are different, and a batch of candidate characteristics such as kurtosis value of component B, variance value of component H, diameter of equilateral circle, skew ness value of component V and so on which is significative to BUS test are chosen, the recognition rate of these single characteristic of each variety is respectively above 85%, 70%, 65%, 50%. It is also showed that the average recognition rate of the three characteristics of shape, color and texture are respectively 32.9%, 30.0% and 28.7%. Some characteristics of color have the best discriminability, while the whole characteristics of size have the poorest one. The method and conclusion in this paper have positive meaning in the area of DUS test of peanut variety." @default.
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- W2481632859 date "2012-04-06" @default.
- W2481632859 modified "2023-09-28" @default.
- W2481632859 title "The Single Characteristic Analysis in the Image Recognition of Peanut Pod Variety" @default.
- W2481632859 doi "https://doi.org/10.1109/iceice.2012.1302" @default.
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