Detection of diseases on cotton leaves and its possible diagnosis

In a research of identifying and diagnosing cotton disease, the pattern of disease is important part in that, various features of the images are extracted viz. the colour of actual infected image, there are so many diseases occurred on the cotton leaf so the leaf colour for different diseases is also different, also there are various other features related to shape of image, also there are different shape of holes are present on the leaf of the image, generally the leaf of infected image have elliptical shape of holes, so calculating the major and minor axis is the major task. The features could be extracted using self organizing feature map together with a back-propagation neural network is used to recognize colour of image. This information is used to segment cotton leaf pixels within the image, now image which is under consideration is well analyzed and depending upon this software perform further analysis based on the nature of this image