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A Survey of Identification of Plant Disease Using Image Processing Techniques and Chameleon Clustering Method


Shailja Maniya , L.D. College of Engineering


Known Nearest Neighbor (K-NN), K-means, K-Medoid, Classification, Image Processing


This work presents overview of different methods to find plant diseases based on leaf characteristics. If these plant diseases are not identified at appropriate time then that can be result into less agriculture productivity. Sometimes even Farmers find it difficult to detect disease in plant. Using image processing, we can detect disease easily using various clustering methods. These methods are only used for detection of diseases using leaves and 65-75 % diseases are on leaves of plant. Here, analysis on different clustering methods i.e. Known Nearest Neighbor (K-NN), K-means and K-Medoid is done which are being used in process for detection of disease. Basic steps includes image acquisition, image preprocessing, feature extraction and statistical analysis and classification based on classifier. All three classification methods detects diseases successfully, But accuracy is different.

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Published in: Conference 10 : NCACSET 2017
Publication Date: 06/05/2017
Page(s): 11-14

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