Image Processing and Pattern Classification Technique in a Machine Vision System that Identifies and Classifies the Plant Diseases Based on the Visual Symptoms.
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Abstract
The proposed method in this paper is to perform the classification using SVM classifier by considering the input features from discrete
wavelet transform, to identify disease in the plant by using visual symptoms. Testing has been done by using 40 images of banana leaf. The
classification accuracy of the proposed method is 97% which is better compare with 86% of accuracy, produced by Back-propagation Neural
Network (BPNN) method.
Keywords: Image Processing, Visual Symptoms, DCT, DWT, SVM, Pattern Reorganization, Back-propagation Neural Network.
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