Research on Rice Leaf Disease Recognition Based on BP Neural Network  

作　　者：Shen Wei-zheng Guan Ying Wang Yan Jing Dong-jun 

机构地区：[1]College of Electrical and Information, Northeast Agricultural University

出　　处：《Journal of Northeast Agricultural University(English Edition)》2019年第3期75-86,共12页东北农业大学学报（英文版）

基　　金：Supported by Quality and Brand Construction of"Internet+County Characteristic Agricultural Products"(ZY17C06)

摘　　要：To solve the problem of mistake recognition among rice diseases, automatic recognition methods based on BP(back propagation) neural network were studied in this paper for blast, sheath blight and bacterial blight. Chose mobile terminal equipment as image collecting tool and built database of rice leaf images with diseases under threshold segmentation method. Characteristic parameters were extracted from color, shape and texture. Furthermore, parameters were optimized using the single-factor variance analysis and the effects of BP neural network model. The optimization would simplify BP neural network model without reducing the recognition accuracy. The finally model could successfully recognize 98%, 96% and 98% of rice blast, sheath blight and white leaf blight, respectively.To solve the problem of mistake recognition among rice diseases, automatic recognition methods based on BP(back propagation) neural network were studied in this paper for blast, sheath blight and bacterial blight. Chose mobile terminal equipment as image collecting tool and built database of rice leaf images with diseases under threshold segmentation method. Characteristic parameters were extracted from color, shape and texture. Furthermore, parameters were optimized using the single-factor variance analysis and the effects of BP neural network model. The optimization would simplify BP neural network model without reducing the recognition accuracy. The finally model could successfully recognize 98%, 96% and 98% of rice blast, sheath blight and white leaf blight, respectively.

关 键 词：rice LEAF disease recognition FEATURE extraction optimization o f CHARACTERISTIC paramete BP NEURAL network 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] S511[自动化与计算机技术—控制科学与工程]