On analysis of wheat leaf infection by using image processing

Abstract

In present scenario, agriculture forms a vital part in India’s economy. More than 50% of India’s population is dependent (directly or indirectly) on agriculture for their livelihood. In India many crops are cultivated, out of which wheat being one of the most important food grain that this country cultivates and exports. Thus it can be seen that wheat forms a major part of the Indian agricultural system and India’s economy. Hence, maintenance of the steady production of above stated crop is very important. The main idea of this project is to provide a system for detecting wheat leaf diseases. The given system will study the leaf image of a wheat plant through image processing and pattern recognition algorithms. Former algorithms are used for extracting vital information from the leaf and the latter is used for detecting the disease that it is infected with. For image processing and segmentation usage of k-means algorithm and canny filter has been suggested. Pattern recognition is achieved through PCA or GLCM and classification through SVM or ANN.