Abstract
An online double-sided identification and eliminating system based on machine vision was developed to identify the unclosed-glumes rice seed by analyzing its double-sided image simultaneously. The vibrating plate and linear vibration conveyor achieved the transfer of rice seed from disordering to spacing, and the identified unclosed-glumes rice seed was eliminated by the blowing jet. Hough linear detection and extracted feature were used to identify the unclosed-glumes rice seeds. The algorithm achieved the accuracy of 88.1% for normal seeds and 87.7% for unclosed-glumes seeds when using double-sided image acquired online. Multi-thread processing was used for double-sided images to shorten the code execution time. The online double-sided identification and eliminating system achieved the average accuracy of 83.7% for normal seeds and 83.3% for unclosed-glumes seeds. Results show that the system has a good adaptation of different rice seed varieties and achieved desired accuracy for online identification and eliminating of unclosed-glumes rice seed.
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