DocumentCode :
2820704
Title :
Identification and counting of pests using extended region grow algorithm
Author :
Martin, A. ; Sathish, D. ; Balachander, C. ; Hariprasath, T. ; Krishnamoorthi, G.
Author_Institution :
Dept. of Master Comput. Applic., Sri Manakula Vinayagar Eng. Coll., Puducherry, India
fYear :
2015
fDate :
26-27 Feb. 2015
Firstpage :
1229
Lastpage :
1234
Abstract :
Agriculture plays most important role in the Indian economy. The agriculture sector of India has covered about 43percent of India´s land area. Digital image processing is the use of computer algorithms like histogram, segmentation, edge detection, fuzzy approach, region based growing and tracking to perform analysis on digital images. In the existing system it is seen that there is a requirement for manual detection and extraction of pest in agricultural field which is not more efficient and accurate. In the proposed work, an integrated pest management using image processing algorithm using extended region based growing to identify the pest and have the counting of the pest to predict the pesticide amount to be used. This extended region grow algorithm provides best identification and counting of the pest.
Keywords :
agriculture; edge detection; fuzzy set theory; image enhancement; image segmentation; Digital image processing; Indian economy; agriculture; edge detection; extended region grow algorithm; fuzzy approach; image histogram; image segmentation; image tracking; Agriculture; Algorithm design and analysis; Image processing; Insects; MATLAB; Sociology; Statistics; agriculture; counting; detection; extended region grow; image processing; pest;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics and Communication Systems (ICECS), 2015 2nd International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-7224-1
Type :
conf
DOI :
10.1109/ECS.2015.7124779
Filename :
7124779
Link To Document :
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