DETECTION OF DISEASED SECTION IN LEAVES USING IMAGE PROCESSING

These days many of the Agro help centres and farmers use different techniques to intensify the agriculture production. Farmers experiences great difficulties in controlling various types of diseases. In this paper we propose an automatic detection of plant diseases using image processing technique. Image processing is the best approach for detecting and diagnosis the diseases in which initially infected region is found, then different features are extracted such as color, texture and shape. These feature extraction uses different techniques like grey level co-occurrence matrix (GLCM), Gabor filter etc. GLCM describes some easily computational texture features based gray time spatial dependencies method. This research used the cooccurrence method to determine whether texture based saturation, contrast, and intensity color features etc. which could be used to identify diseased and normal leaves under experimental conditions. From the texture statistics, the presence of diseases on the plant leaf is evaluated. It includes several steps viz. image acquisition, image pre-processing and features extraction and classification