Publication: Application of image processing and computer vision on rice seed germination analysis
Issued Date
2016-01-01
Resource Type
ISSN
09739769
09734562
09734562
Other identifier(s)
2-s2.0-84994101991
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Mahidol University
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SCOPUS
Bibliographic Citation
International Journal of Applied Engineering Research. Vol.11, No.9 (2016), 6800-6807
Suggested Citation
B. Lurstwut, C. Pornpanomchai Application of image processing and computer vision on rice seed germination analysis. International Journal of Applied Engineering Research. Vol.11, No.9 (2016), 6800-6807. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/40619
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Title
Application of image processing and computer vision on rice seed germination analysis
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Abstract
© Research India Publications. This paper presents a machine vision application designed for rice seed germination analysis by using image processing and computer vision technology. The application is called “Rice Seed Germination Analysis (RSGA)”. RSGA consists of five main processing modules which are image acquisition, image preprocessing, feature extraction, quality control analysis and quality results. The experiments is conducted on six variation Thai rice seed species of CP111, RD41, Chiang Phatthalung, Sang Yod Phattalung, Phitsanulok 2 and Chai Nat 1 in Bangkok and Chiangmai province of Thailand. RSGA extracts four main features which are color, size, shape, and texture. Then, RSGA applies Artificial Neural Network techniques in crop germination prediction. The precision rate is 93.06 percent, with the speed 8.31 seconds per image.