Research on Rice Detection Technology Based on Machine Vision

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Abstract:

Detection of rice kernel domestic mainly rely on manual measurement using a ruler or vernier caliper tool, which use the ruler measurement of human error, and the measurement of the twisted grain rice vernier caliper is limited. Manual measurement are difficult problems, but also low efficiency. This study analyzes the current research on appearance quality of rice by using machine vision technology mainly focuses on the aspects of rice kernel, chalkiness, yellow rice and other characteristics, realized the accurate detection and obtain rice information quickly by using the machine vision technology, improves the speed and precision of detection, especially detection effect the grain shape distortions.

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Periodical:

Advanced Materials Research (Volumes 1030-1032)

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1788-1791

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Online since:

September 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Yukuan Luo, Zhiwei Zhu, Neng Chen, and etc. Grain type and quality characteristics of rice in China,. Chinese Journal of Rice Science, Vol. 18(2008), p.135.

Google Scholar

[2] GB/T 17891-1999. State Standard of the Peoples Republic of China—High quality paddy,. Beijing: The State Bureau of quality supervision, (1999).

Google Scholar

[3] Jianhua Chen, Qing Yao, Shaojun Xie, and etc. Application of machine vision in the detection of rice kernel. Chinese Journal of rice science, Vol. 21(2007), p.669.

Google Scholar

[4] Yun Ling. Study on appearance quality detection based on machine vision of grain. Beijing: Agriculture University of China, (2004).

Google Scholar

[5] Ming Sun, Yun Ling, Yiming Wang. White rice chalkiness detection based on computer vision technology in MATLAB environment. The Chinese society of Agricultural Engineering, Vol. 18 (2002), p.146.

Google Scholar

[6] Suqing Yang. The research on rice appearance quality computer vision detection. Yangling: Northwest A&F University, (2005).

Google Scholar

[7] Yun Ling, Yiming Wang, Ming Sun and etc. Rice appearance quality detection device based on machine vision Vol. 36(2005), p.89.

Google Scholar

[8] Shuso Kawamura, Motoyasu Natsuga, Kazuhiro Takekura, and etc. Development of an automatic rice-quality inspection system. Computers and Electronics in Agriculture, Vol. 40(2003), p.115.

DOI: 10.1016/s0168-1699(03)00015-2

Google Scholar

[9] Yanhong Wu, Muhua Liu, Jun Yang, and etc. Rice appearance quality detection based on computer vision. The Chinese society of agricultural machinery, Vol. 38(2007), p.107.

Google Scholar

[10] Yingting Liu, Weiming Ding, Mingxia Shen. Rice appearance quality evaluation method for multiple structure based on Neural Network. Chinese Journal of rice science, Vol. 23(2009), p.440.

Google Scholar

[11] Lijiang Chan, Tiegen Liu, Lei Wang, and etc. Using the flatbed scanner and image processing method for the detection of rice kernel. Infrared and laser engineering, Vol. 36(2006), p.402.

Google Scholar