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Paper Details

Paper Title
LEAF DISEASES DETECTION
Abstract
the aim of this project is to style, implement and judge a picture process code primarily based resolution for automatic detection and classification of plant disease. But studies show that hoping on pure naked-eye observation of consultants to observe and classify diseases may be time intense and dearly-won, particularly in rural areas and developing countries. Thus we tend to gift quick, automatic, low-cost and correct image process primarily based resolution. Resolution consists of 4 main sections; within the 1st phase we tend to produce a color transformation structure for the RGB leaf image then, we tend to apply color area transformation for the color transformation structure. Next, within the second section, the photographs are segmental mistreatment the K-means clump technique. Within the third section, we tend to calculate the feel options for the segmental infected objects. Finally, within the fourth section the extracted options are knowledgeable a pre-trained neural network.
KeyWord
Leaf diseases, Image pre-processing, Image segmentation, Segmentation.
Others Details
Paper Id : 25495
Author Name : Miss.Sayali Walhekar
Co-Author Name(s) : Miss.Sayali JoshiMiss.Nikita GawadeMiss. Saloni Chillawar
Volume/Issue No : Volume 05 Issue 04
Page No : 89-92
DOI Number : DOI:10.21090/IJAERD.25495
Publication Date : 2018-04-06
License : This work is licensed under a Creative Commons Attribution 4.0 International License.
website : http://www.ijaerd.com/index.php
Impact Factor : 4.72, SJIF-2016
ISSN Details : eISSN: 2348-4470, pISSN:2348-6406