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In this paper, we propose the target detection method using image displacement, and classification method using SURF(Speeded Up Robust Features) feature points and BAS(Beam Angle Statistics) in infrared images. The SURF method that is a typical correspondence matching method in the area of image processing has been widely used, because it is significantly faster than the SIFT(Scale Invariant Feature Transform) method, and produces a similar performance. In addition, in most SURF based object recognition method, it consists of feature point extraction and matching process. In proposed method, it detects the target area using the displacement, and target classification is performed by using the ∙1 :  ∙ :  ∙ : 2014. 6. 19,  : 2014. 7. 16,  : 2014. 9. 19. * (Samsung Thales Co.) **  (Dept. of CSE, Hanyang University) 44 Journal of The Korea Society of Computer and Information November 2014 geometry of SURF feature points. The proposed method was applied to the unmanned target detection/recognition system. The experimental results in virtual images and real images, we have approximately 73~85% of the classification performance. ▸

The Target Detection and Classification Method Using SURF Feature Points and Image Displacement in Infrared Images