Identification of Cotton Crop Diseases and Provide their Remedies using Kmeans Clustering

Rani Pagariya, Mahip Bartere


Best quality Best quality cotton produces best fiber. Hence it is important that cotton produced in farms is of best quality. Nowadays crops face many diseases. This project mainly focuses on detection of diseases. Since only detection is not sufficient and hence possible remedies are also provided. In this we are mainly using K-means clustering algorithm for Image segmentation technique for processing images and feature extraction for detecting diseases. The diseases are identified with the help of features extracted by machine learning approach. The Extracted features are going to help to find out diseases. Mainly two types of diseases focused over here viz.:- leaf based diseases and diseases due to pest. This work descries that how can we do the automatic detection of Crop diseases as this can gives much benefits in monitoring large fields of crops and detect the symptoms of diseases. Fast, Automatic, Less Expensive and accurate method to detect, classify, identify the crop diseases.


Keywords: Feature extraction, K-means clustering, image processing, segmentation.

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