Cotton Leaf Disease Detection and Classification Using Image Processing Full Matlab Code

ABSTRACT

            Cotton is one of the most important fiber crop which is used as raw material in textile industries. But, now-a-days cotton is facing number of problems related to the healthy growth of crop due to diseases. These diseases are reducing the productivity of cotton crop and farmers are getting suffered financially due to this crop loss. Agriculture is an important source of livelihood where 65% population is depend on it. The crop loss due to disease is increasing day by day which affects on the quality and productivity of crop. As diseases on the crop are certain, the early disease detection of the crop plays major role to control the loss in agriculture. In the proposed disease detection system, the work is carried out on cotton leaves. Initially the infected region is captured and pre-processed. During segmentation, leaf as well as diseased part is segmented using k means clustering method and different features are extracted such as color and texture with the help of color-co-occurrence method. Finally classification technique is used for detecting the diseases with the help of SVM (Support Vector Machine) classifier.

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Mr. Roshan P. Helonde

Mobile: +91-7276355704

WhatsApp: +91-7276355704

Email: roshanphelonde@rediffmail.com