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《Journal of Anhui Agricultural Sciences》 2011-28
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Research on Recognition of Rhizocotonia solani Based on Support Vector Machine

LIU Ting-ting(School of Software and Microelectronics,Beijing University,Beijing 100093)  
[Objective]The study aimed to research the automatic recognition of Rhizocotonia Solani by support vector machine(SVM) so as to make up the defect of artificial recognition and increase the accuracy and efficiency of recognition.[Method]With R.Solani as the studied object,firstly,the method based on the vector median filtering was used to pre-treat the image of R.Solani,then the fuzzy c-mean clustering method was used to make for the gray image segmentation in the image segmentation stage and the feature parameters which represented the lesion were extracted from three aspects such as color,texture and shape,finally the SVM recognition method was used to identify R.Solani and was compared with the recognition method based on BP neural network.[Result]The SVM recognition method showed the recognition rate of 95.00%,which is better than that of BP neural network(91.88%).[Conclusion]The recognition of R.Solani based on SVM could not only make up the defect of artificial recognition,but also increase the accuracy and efficiency of recognition,which showed the broad application prospects.
【Fund】: 国家863项目 “大田作物智能诊断技术系统研究与应用”(2007AA10Z237)
【CateGory Index】: S435.111.4;TP18
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