【摘 要】
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To solve the problem of mistake recognition among rice diseases, automatic recognition methods based on BP (back propagation) neural network were studied in thi
【机 构】
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College of Electrical and Information, Northeast Agricultural University, Harbin 150030, China
论文部分内容阅读
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.
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