Abstract
This paper systematically studies maize seeds varieties identification technology and algorithms using advanced machine vision technology. A multi-object contour extraction algorithm adapting to maize seeds varieties identification was proposed. Geometric features and color features parameters of maize seeds were defined and analyzed, and a multi-object geometric features and color features extraction algorithm is realized. Maize seeds image processing strategies and varieties identification algorithms, which is based on the machine vision, is optimized. The precision and speed of maize seeds varieties identification is improved. Through maize seeds varieties identification test on four species including Nongda 108, Ludan 981 and Zhengdan 958, identification accuracy is more than 95%.
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References
David Pinentel. World resources and food loses to pests, Ecology and management of food industry pests, 1991, 5–11
Feng Wanyu, Xiao Jianhua, Liu Yun, et al. Studying the diagnostic expert system of swine diseases on based of integrated technology, Journal of stock and veterinarian, 2007, 26(2):27–28(in Chinese)
Gao Lingwang, Shen Zuorui, Liu Zhiqi. Design and development of Taxokeys: a dichotomous-reasoning-based multimedia expert system assisting insect identification and taxonomic study, Entomology, 2003, 46(5):644–648(in Chinese)
J. L. Gonzalez-Andujar, C. Fernandez-Quintanilla, J. Izquierdo, et al. SIMCE: An expert system for seedling weed identification in cereals, Computers and electronics in agriculture, 2006, 54:115–123
J. Liebowitz, S. I. Baek. The protocol multimedia expert system, The New Review of Applied Expert Systems, 1996, 1:3–17
J. W. Travis, E. G. Rajotte, R. Bankert, et al. Penn State apple orchard consultant expert system: The design and function of the pest management module, Plant Disease, 1992, 76(6):545–554
Li Daoliang, Fu Zetian, Duan Yanqing. Fish-Expert: a web-based expert system for fish disease diagnosis, Expert Systems with Applications, 2002, 23:311–320
Li Kaibing, Gao Lingwang, Shen Zuorui, et al. Development of the expert system for assistant identification of insects of scolytidae based on the platform of Toxakeys, Plant quarantine, 2006, 20:17–19(in Chinese)
Li Shulong, Zhao Zhimo. Review and prospect of research and control of inserts in storehouse in China, Entomological Knowledge, 2000, 37(2):84–88(in Chinese)
Li Zhihong, Zhang Baofeng, Chen Hongjun. Expert systems and assistant identifications of quarantine pests, Plant quarantine, 2001, 15(4):235–239(in Chinese)
Liu Yuexian, Shen Zuorui, Cai Xinyan. Research of Agricultural pests assistant identification and control consultation system, Computers and Agriculture, 2002, 1:9–11 (in Chinese)
Tang Yuechen, Chen Jianwu. Weeds identification expert system, Journal of Fujian Agricultural University, 1999, 28(3):330–334(in Chinese)
Xu Guogan. Stored pests quarantine, Grain storage, 1994, 23:100–104(in Chinese)
Yin Wenya, Wang Xiaoping, Zhou Chengai. Pests in storehouse and status of chemical control, Hunan Agricultural Science, 2002, 6:54–56(in Chinese)
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© 2009 Springer-Verlag US
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Liu, X., Wang, Y., Su, Q., Wang, Z. (2009). Study On Identification System Of Maize Seedsvarieties Based On Machine Vision. In: Zhao, C., Li, D. (eds) Computer and Computing Technologies in Agriculture II, Volume 3. CCTA 2008. IFIP Advances in Information and Communication Technology, vol 295. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0213-9_72
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DOI: https://doi.org/10.1007/978-1-4419-0213-9_72
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