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Proceedings Paper

Corn leaf disease spot recognition comparative study of Bayesian classification and fuzzy pattern recognition
Author(s): JingFu Zhu; BaiYi Zhang; ZhaoWu Guo
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Paper Abstract

Crop diseases occurrence have a great impact on Agricultural Production. Using the technology based on machine recognition to identify crop diseases automatically has important significance on agricultural production. The principles of the Bayesian Classification and the Fuzzy Pattern Recognition are introduced in this paper. Classification on 5 kinds of corn leaf diseases spot respectively are implemented based these two methods. The results show that the average recognition rate of Fuzzy Pattern Recognition is higher than Bayesian Classification’s on corn leaf disease spot. Average recognition rate of the 5 kinds of corn leaf disease spot is more than 93%.

Paper Details

Date Published: 19 March 2013
PDF: 5 pages
Proc. SPIE 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 87621H (19 March 2013); doi: 10.1117/12.2019660
Show Author Affiliations
JingFu Zhu, Heilongjiang Bayi Agriculture Univ. (China)
BaiYi Zhang, Heilongjiang Bayi Agriculture Univ. (China)
ZhaoWu Guo, Changsha Univ. (China)


Published in SPIE Proceedings Vol. 8762:
PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering
Honghua Tan, Editor(s)

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