Detection and classification of diseases in plants using image processing and machine learning techniques

Disease identification in plants is very essential for preventing the loss in yield of the agricultural products. It is difficult to monitor the plant diseases manually at each stage, which requires more effort and time. The main objective of this work is to analyze and detect the diseases that affect the plants using image processing and machine learning techniques. The symptoms of plant diseases are identified and segmented using edge and color based image processing methods. Relevant features from the segmented diseased leaf portion are extracted and the type of disease is classified using multi-class Support Vector Machine. In this research work the plant diseases caused by different pathogens such as bacteria, fungus and virus are analyzed for early and periodical detection of plant diseases.