DocumentCode :
3587721
Title :
Regularized logistic regression based classification for infrared images
Author :
Mirzaei, Golrokh ; Jamali, Mohsin M. ; Gorsevski, Peter V. ; Frizado, Joseph ; Bingman, Verner P.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Toledo, Toledo, OH, USA
fYear :
2014
Firstpage :
487
Lastpage :
490
Abstract :
There is an increase in the bird and bat mortality near wind farms. It is desirable to document and quantify behavior and activity of birds/bats near wind farms. Infrared Imaging is a useful monitoring method for this purpose. However, IR images do not provide information as whether the target is a bird, bat or insect. A logistic regression classifier is used to provide category information of the targets. There are no priori known database of images available for birds, and bats. Features of targets are extracted and used for classification purpose. A database of labeled category based on the features has been created.
Keywords :
computerised monitoring; feature extraction; image classification; infrared imaging; regression analysis; visual databases; wind power plants; IR images; bat mortality; bird mortality; image database; infrared images; labeled category database; logistic regression classifier; monitoring method; regularized logistic regression based classification; target category information; target feature extraction; wind farms; Birds; Databases; Decision support systems; Feature extraction; Infrared imaging; Monitoring; Wind farms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2014 48th Asilomar Conference on
Print_ISBN :
978-1-4799-8295-0
Type :
conf
DOI :
10.1109/ACSSC.2014.7094491
Filename :
7094491
Link To Document :
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