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Journal of Zhejiang University SCIENCE A 2004 Vol.5 No.6 P.663~667

http://doi.org/10.1631/jzus.2004.0663


Machine vision inspection of rice seed based on Hough transform


Author(s):  CHENG Fang, YING Yi-bin

Affiliation(s):  College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China

Corresponding email(s):   fcheng@zju.edu.cn

Key Words:  Hough transform, Incompletely closed glumes, Rice seed, Machine vision


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CHENG Fang, YING Yi-bin. Machine vision inspection of rice seed based on Hough transform[J]. Journal of Zhejiang University Science A, 2004, 5(6): 663~667.

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author="CHENG Fang, YING Yi-bin",
journal="Journal of Zhejiang University Science A",
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year="2004",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2004.0663"
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%DOI 10.1631/jzus.2004.0663

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T1 - Machine vision inspection of rice seed based on Hough transform
A1 - CHENG Fang
A1 - YING Yi-bin
J0 - Journal of Zhejiang University Science A
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EP - 667
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DOI - 10.1631/jzus.2004.0663


Abstract: 
A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.

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Reference

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