Paddy is a keystone for human beings. The work proposes for detecting paddy leaf diseases accurately using image processing techniques. The system is developed to provide a software solution for automatic leaf disease detection and classification of plant leaf diseases. By this approach one can detect the disease at a very primary stage and thus can take necessary steps in time to minimize the loss of production. The technique is to develop a diagnosis system to recognize the paddy diseases, which are Leaf Blast Disease, Brown-Spot Disease. At first, an image of a paddy leaf is captured and transferred to the host, the segmentation process for the disease spots are carried out using Gaussian blur function, Color and Texture extraction feature for the segmented image is done to classify the disease for the leaf. Based on the threshold value, both database and input images are compared so that the classification is identified. After completing disease identification, consultative treatment for the disease is provided.