Study and Analysis of Cotton Leaf Disease Detection Using Image Processing
The detection of plant leaf disease is a very important factor to prevent serious outbreak. Most plant diseases are caused by fungi, bacteria, and viruses. Traditionally farmer visually checks the disease. This paper presents an approach for careful detection of diseases and timely handling to prevent the crops from heavy losses. The diseases on the cotton are critical issue which makes the sharp decrease in the production of cotton. So for the study, of interest is the leaf rather than whole cotton plant. About 80 95% of diseases occurred on the cotton leaves are like Alternaria, Cercospora, Red spot, white spot and Yellow spot on the Leaf. In this Paper initially the image of the infected leaf is taken& the image pre processing is done taking the histogram equalization is applied to increase the contrast in low contrast image. K means clustering algorithm is used for segmentation which classifies objects based on a set of features into K number of classes and finally classification is performed using Neural network. Thus image processing technique is used for detecting diseases on cotton leaves is simple and accurately.