Disease Detection and Classification inCotton Plants using Unsupervised Learning-based Color and Texture Feature Extraction
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Abstract
In this, we have used SVM classifier to identify the pest and type of disease in cotton plant. Image acquisition devices are used to acquire images of plantations at regular intervals. These images are then subjected to preprocessing using median filtering technique. The pre-processed leaf images are then segmented using K-means clustering method. Then the color features(mean, skewness), texture features such as energy, entropy, correlation, contrast, edges are extracted from diseased leaf image using gray scale matrix (GSM) in the texture and then compared with normal cotton leaf image
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