JOURNAL ARTICLE

Tea Leaf Disease Segmentation by using Color and Region’s Mean Based Segmentation (CRM)

Velmurugan PDr.M.Renuka Devi

Year: 2019 Journal:   International Journal of Recent Technology and Engineering (IJRTE) Vol: 8 (4)Pages: 209-212

Abstract

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.

Keywords:
Segmentation Artificial intelligence Image segmentation Peak signal-to-noise ratio Pattern recognition (psychology) Computer science Region growing Image (mathematics) Scale-space segmentation Homogeneous Computer vision Mathematics

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Topics

Smart Agriculture and AI
Life Sciences →  Agricultural and Biological Sciences →  Plant Science
Spectroscopy and Chemometric Analyses
Physical Sciences →  Chemistry →  Analytical Chemistry
Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
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