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Detection of Diseases on Cotton Leaves and its Possible Diagnosis
Viraj Ashokrao Gulhane, Ajay A. Gurjar
Pages - 590 - 598     |    Revised - 01-11-2011     |    Published - 15-12-2011
Volume - 5   Issue - 5    |    Publication Date - November / December 2011  Table of Contents
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KEYWORDS
Image Processing Application in Agriculture Scienc, Coading Analysis and Recognition, Biomedical Image Processing
ABSTRACT
In a research of identifying and diagnosing cotton disease, the pattern of disease is important part in that, various features of the images are extracted viz. the color of actual infected image, there are so many diseases occurred on the cotton leaf so the leaf color for different diseases is also different, also there are various other features related to shape of image, also there are different shape of holes are present on the leaf of the image, generally the leaf of infected image have elliptical shape of holes, so calculating the major and minor axis is the major task . The features could be extracted using self organizing feature map together with a back-propagation neural network is used to recognize color of image. This information is used to segment cotton leaf pixels within the image, now image which is under consideration is well analyzed and depending upon this software perform further analysis based on the nature of this image.
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Mr. Viraj Ashokrao Gulhane
Sipna college of engineering and technology - India
virajgulhane@live.com
Dr. Ajay A. Gurjar
Sipna College of engineering and Tech. - India