Identification of plant leaf diseases using image processing techniques

Image processing is a diverging area where researches and advancements are taking a geometrical progress in the agricultural field. Various researches are going on vigorously in plant disease detection. Identification of plant diseases can not only maximize the yield production but also can be supportive for varied types of agricultural practices. This paper proposes a disease detection and classification technique with the help of machine learning mechanisms and image processing tools. Initially, identifying and capturing the infected region is done and latter image preprocessing is performed. Further, the segments are obtained and the area of interest is recognized and the feature extraction is done on the same. Finally the obtained results are sent through SVM Classifiers to get the results. The Support Vector Machines outperforms the task of classification of diseases, results show that the methodology put forward in this paper provides considerably better results than the previously used disease detection techniques.