DocumentCode
3303607
Title
Extension Theory for Classification of the Stored-Grain Insects
Author
Zhang, Hongtao ; Hu, Yuxia
Author_Institution
Sch. of Electr. Power, North China Univ. of Water Conservancy & Electr. Power, Zhengzhou, China
fYear
2010
fDate
24-25 April 2010
Firstpage
758
Lastpage
760
Abstract
The design of the classifier is one of the important parts of the online detection system of the stored-grain insects based on the image recognition technology. The classification of the insects was of many image feature parameters, and the mixing degree among feature parameters of various species of the insects was large. The extension theory was proposed to be applied to the automatic classification of the insects. A method that constructed the matter element matrix of the insects was put forward based on the mean and variance of the image features. After calculating the correlation degrees between the insect to be recognized and the nine species of insects, the insect could be recognized by the maximum integrated correlation degree criterion. The experiment confirms that the recognition of the insects based on the extension theory is practical and feasible by the training and analyzing of the samples of the insects.
Keywords
Artificial neural networks; Image recognition; Insects; Machine vision; Man machine systems; Pollution; Set theory; Stability; Water conservation; Water storage; classification; extension theory; matter-element matrix; stored-grain insects;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
Conference_Location
Kaifeng, China
Print_ISBN
978-1-4244-6595-8
Electronic_ISBN
978-1-4244-6596-5
Type
conf
DOI
10.1109/MVHI.2010.40
Filename
5532478
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