CIELuv color space for identification and segmentation of disease affected plant leaves using fuzzy based approach

Economy of developing countries mainly depends on the agriculture productivity. The identification and control of plant disease plays a vital role in improving the quality and quantity of agriculture productivity. It is very difficult to monitor or detect the crop disease using the traditional manual methods. Computer based automated techniques for the identification of plant disease is advantageous as it detects very early stage of symptoms of plant diseases and also it lessens the burden of workers in monitoring the large fields. Image processing techniques can be applied to solve the problem of identification and extraction of the affected parts of plants in efficient manner. In this work, fuzzy based method for the early identification and segmentation of disease affected plant leaves is proposed.