Corn leaf disease spot recognition comparative study of Bayesian classification and fuzzy pattern recognition

JingFu Zhu; BaiYi Zhang

doi:10.1117/12.2019660

19 March 2013 Corn leaf disease spot recognition comparative study of Bayesian classification and fuzzy pattern recognition

JingFu Zhu, BaiYi Zhang

Author Affiliations +

Proceedings Volume 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering; 87621H (2013) https://doi.org/10.1117/12.2019660
Event: Third International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2013), 2013, Sanya, China

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%.

Citation Download Citation

JingFu Zhu and BaiYi Zhang "Corn leaf disease spot recognition comparative study of Bayesian classification and fuzzy pattern recognition", Proc. SPIE 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 87621H (19 March 2013); https://doi.org/10.1117/12.2019660

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