Classification of Cotton Leaf Spot Disease Using Enhanced HPCCDD Algorithm
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
Cotton is the most crucial commercial crop of India and all over the states. Cotton disease analysis using most probably of the environment has been utilizes significant techniques available in image processing , data mining and signal processing areas. The image is converted into pixels to detect the disease correctly and report it to the farmers. This work focusses on new algorithm named improved HPCCDD (Homogeneous Pixel Counting Algorithm for Cotton Diseases Detection) (ie)., feature extraction using PSO algorithm, which recognizes the features available in the affected image by matching the threshold values assigned to the RGB features. Finally performance evaluation is carried out 100 images and 500 images to check the accuracy of the algorithm, with other existing algorithms.
Authors and Affiliations
Dr. P. Revathi
Keywords
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