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A Novel Plant Leaf Ailment Recognition Method using Image Processing Algorithms

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Title A Novel Plant Leaf Ailment Recognition Method using Image Processing Algorithms
 
Creator Thenmozhi, S
Lakshmi, R Jothi
M V, Kumudavalli
Ibrahim, Irshadh
Mohan, Rekha
 
Subject Artificial Neural Network
Classification
Image Processing
Plant disease detection
 
Description 979-984
In the 21st Century, agriculture still remains the major source of food for human beings and it has far shadowed other sources such as hunting, fishing and gathering. Since environmental conditions are beyond the scope of human control, plant illness identification is acting as a critical position in the agricultural field. This paper suggests a method to replace the traditional methods of identifying disease through the use of “image-processing” techniques. In this study, an image of the leaf of a diseased plant has been taken using a digital camera. Three segmentation algorithms namely Green Pixel Masking, “CIE L*a*b colour space” extraction and H element of HSV extraction have been used to split the image into diseased and healthy regions. The diseased region is then used to calculate 13 parameters which are utilized as inputs by a pre-trained neural network which utilizes “feed-forward back propagation algorithm” to determine the final output. The proposed methodology has achieved a maximum accuracy of 95.62% for Apple leaves, 91.62% for Grape leaves and 91.1% for Tomato leaves.
 
Date 2021-11-17T06:12:16Z
2021-11-17T06:12:16Z
2021-11
 
Type Article
 
Identifier 0975-1084 (Online); 0022-4456 (Print)
http://nopr.niscair.res.in/handle/123456789/58525
 
Language en
 
Publisher CSIR-NIScPR
 
Source JSIR Vol.80(11) [November 2021]