Classification and Segmentation Approach for Plant Disease Detection

The infections in plants leafs can be detected with the help of plant disease recognition system. Different phases such as textural feature scrutiny, segmentation and classification are involved in plant infection or disease recognition. This study utilizes the KNN classifier along with GLCM algorithm for the plant disease detection. The projected method primarily takes pre-processed picture in form of input. In the subsequent step, texture feature scrutiny is performed with the help of GLCM algorithm. The area based segmentation is executed through K-mean clustering and KNN classifier is implemented for the infection forecasting. MATLAB programming is used for the implementation of projected approach. The reproduction outcomes demonstrate precision ratio up to 97 percent.