Target Recognition of FLIR Images on Radial Basis Function Neural Network

Authors:
Jun Liu;Xiyue Huang;Yong Chen;Naishuai He
Affiliations:
Automation College, Chongqing University, Chongqing 400030, China;Automation College, Chongqing University, Chongqing 400030, China;Automation College, Chongqing University, Chongqing 400030, China;Automation College, Chongqing University, Chongqing 400030, China
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Year:
2007

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Fundamentals of digital image processing

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Neural Processing Letters

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Abstract

The study of small target recognition in low SNR (Signal Noise Ratio) is the key problem about processing of forward-looking infrared (FLIR) images information. Eight features of objects based on IR radiation characteristics and wavelet-based are presented. These features are used to a radial basis function (RBF) network as input for learning and classification. The propose recognition algorithm is invariant to the translation, rotation, and scale channel of a shape. Experiments by real infrared images and noisy images are performed, and recognition results show that the method is very effective.