Rice Appearance Quality Detection Technology Based on Muti-demensional Features
Image processing technology has the advantage of high efficiency in rice appearance quality detection, but it is easily affected by weak light intensity. In order to improve the image quality, a new data fusion algorithm is proposed, which realizes the segmentation of rice sample and background, eli...
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| Main Authors: | , |
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| Format: | Article |
| Language: | Chinese |
| Published: |
Harbin University of Science and Technology Publications
2021-10-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2017 |
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| Summary: | Image processing technology has the advantage of high efficiency in rice appearance quality detection, but it is easily affected by weak light intensity. In order to improve the image quality, a new data fusion algorithm is proposed, which realizes the segmentation of rice sample and background, eliminates the noise to the maximum extent, and improves the accuracy of subsequent detection function. A set of automatic recognition functions of broken rice, crack, chalkiness and machining accuracy are realized. In this expe1-iment, 6 kinds of rice were selected as test samples, 10 grains of rice were randomly selected as a group, and 4 groups of samples were selected for each test. After many tests, the results show that the detection accuracy of the system for broken rice rate of random rice samples is 97. 01 % , rice seed detection accuracy is 97. 60%, crack detection accuracy is 98. 22%, which is better than the traditional manual detection method. The system provides a technical basis for further improving the automatic detection technology of rice quality. |
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| ISSN: | 1007-2683 |