Multi Classifier Based Disease Recognization on Cotton Leaves

Diagnosis of plant disease is a task of identifying the disease in the leaf or fruit or vegetable. About 42 percent of the world’s agriculture harvest is destroyed yearly by disease and pest. However, losses of harvest can be minimized and specific treatments can be applied if plant diseases are correctly identified early. Manual identification of disease in the plant is not only time consuming but also does not give accurate result. So, providing fast, automatic and accurate solution using image processing techniques can be a good realistic significance. Automatic identification of diseases using image processing techniques can be done by using five methods like Image Acquisition, Image Pre- processing, image segmentation, Feature extraction and classification using multiple classification algorithms. This paper shows the result of research conducted on detection of diseases on cotton leaves found in Khandesh region with the help of different classifiers such as Neural Network and Naive Bayes classifier and their combinations.