Open AccessTea Leaf Disease Segmentation by using Color and Region’s Mean Based Segmentation (CRM)
Author(s) -
V.P. Fedosov V.P.,
Dr.M.Renuka Devi
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d6494.118419
Subject(s) - segmentation , artificial intelligence , image segmentation , peak signal to noise ratio , pattern recognition (psychology) , computer science , region growing , image (mathematics) , scale space segmentation , computer vision , mathematics
In agriculture image processing and Datamining play an important role. Prediction of crop yield prediction is very important in tea production. Image segmentation is used to segment the disease affected region in the leaf. It segment image into various homogeneous region. In this paper color and Region’s mean based segmentation technique is introduced to subtract background and fore ground. This new approach is analyzed and compared based on five performance metrics such as PSNR (Peak Signal to Noise Ratio) Value, Rand Index (RI), precision, recall and accuracy. The proposed method gave better accuracy than other methods.