Forward-looking infrared target recognition based on histograms of oriented gradients

Zhiguo Cao; Xuan Zhang; Wenwu Wang

doi:10.1117/12.901811

8 December 2011 Forward-looking infrared target recognition based on histograms of oriented gradients

Zhiguo Cao, Xuan Zhang, Wenwu Wang

Proceedings Volume 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis; 80030S (2011) https://doi.org/10.1117/12.901811
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

This paper analyzes the difference between the imaging mechanism of the infrared images and that of the visible light images, and find that it is important to extract the stable and reliable common feature for object recognition. Then we propose a target recognition algorithm based on histograms of oriented gradients (HOG) which evaluates normalized local histograms of image gradient orientations in a dense grid. Last we adopt linear SVM trained for a binary object/non-object classifier and detect the object in the forward-looking infrared (FLIR) images. The experiment results suggest that the proposed approach has high rates of detection. Furthermore, we study how to select positive and negative samples for a better performance.

Citation Download Citation

Zhiguo Cao, Xuan Zhang, and Wenwu Wang "Forward-looking infrared target recognition based on histograms of oriented gradients", Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030S (8 December 2011); https://doi.org/10.1117/12.901811

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