An Improved Leaf Disease Detection Using Collection Of Features And SVM Classifiers
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
Leaf diseases weaken trees and shrubs by interrupting chemical change, the method by that plants produce energy that sustains growth and defense systems and influences survival. Problem can be resolved when provided with the remedial action in time and this can be achieved with the introduction of technology in the system. This paper presents an improved method for leaf disease detection using an adaptive approach. The algorithm presented used to preprocess, segment and extract information from the preprocessed image. The segmentation is done using K-Means algorithm to achieve different clusters. The shape feature and color texture features are extracted from the affected reasons and send to the SVM classifier. The detection task performed and experimental results prove that the proposed method is efficient in reaching convergence.
Authors and Affiliations
Sandeep B. Patil, Santosh Kumar Sao
Keywords
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