Agricultural productivity is something on which our economy highly depends. This is the one of the reasons that disease detection in plants plays an important role in agriculture field. Insect pests are dangerous for the overall growth of the crops. Several Integrated Pest Management strategies have been tailored for the effective management of insect pests under filed condition. But, a prime method to protect the crop may be the regular monitoring of the crop for the occurrence of the insect pests to understand the health of the crop. Early detection of insect pest infestation to evolve suitable management techniques, therefore, would be an important step towards successful implementation of pest control strategies at appropriate time targeting the most vulnerable stage of the insect pest. Further, if the insect pests are detected at their early stage, appropriate measures can be taken to protect the crop from future damage that can be caused by the insect thereby immense crop loss can be minimized. This paper presents an algorithm for image segmentation technique which is used for automatic detection and classification of plant leaf diseases. It also covers survey on different diseases classification techniques that can be used for plant leaf disease detection. The diagnosis of plant disease by computer vision using image processing methodology is a key for timely intervention and treatment of healthy agricultural procedure and to increase the yield by natural means. Digital image processing has three basic steps: processing, analysis and understanding. Image processing contains the pre-processing of the plant leaf as segmentation, color extraction, diseases specific data extraction and filtration of images. Image analysis generally deals with the classification of diseases