Rape Plant Disease Recognition Method of Multi-Feature Fusion Based on D-S Evidence Theory
AbstractIn view of the low accuracy and uncertainty of the traditional rape plant disease recognition relying on a single feature, this paper puts forward a rape plant disease recognition method based on Dempster-Shafer (D-S) evidence theory and multi-feature fusion. Firstly, color matrix and gray-level co-occurrence matrix are extracted as two kinds of features from rape plant images after processing. Then by calculating the Euclidean distance between the test samples and training samples, the basic probability assignment function can be constructed. Finally, the D-S combination rule of evidence is used to achieve fusion, and final recognition results are given by using the variance. This method is used to collect rape plant images for disease recognition, and recognition rate arrives at 97.09%. Compared with other methods, experimental results show that the method is more effective and with lower computational complexity. View Full-Text
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Hu, M.; Bu, X.; Sun, X.; Yu, Z.; Zheng, Y. Rape Plant Disease Recognition Method of Multi-Feature Fusion Based on D-S Evidence Theory. Math. Comput. Appl. 2017, 22, 18.
Hu M, Bu X, Sun X, Yu Z, Zheng Y. Rape Plant Disease Recognition Method of Multi-Feature Fusion Based on D-S Evidence Theory. Mathematical and Computational Applications. 2017; 22(1):18.Chicago/Turabian Style
Hu, Min; Bu, Xiangyu; Sun, Xiao; Yu, Zixi; Zheng, Yaona. 2017. "Rape Plant Disease Recognition Method of Multi-Feature Fusion Based on D-S Evidence Theory." Math. Comput. Appl. 22, no. 1: 18.