Published Paper Details:

The prevention and control in plant disease plays vital role in architectural filed. Accurate and rapid diagnostic of disease helps to control the disease at early stage. The detection of plant disease using automatic technique is beneficial and reduces large work of monitoring each individual plant in the farm. A combined usage of image processing techniques and machine learning techniques helps to recognize the disease. This paper includes the study of existing systems for plant disease detection. The study includes various technique used for disease detection its advantages and limitations. Based on the existing work analysis, a new system is proposed. In the proposed system, plant leaf image features are extracted using Gabor filter and watershed segmentation algorithm which includes the color, texture and intensity property of image. Based on the extracted features the image is compared with existing disease training data. The test image is labeled with the related disease using classification technique.