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28 April 2009 High speed automatic target recognition based on anisotropic diffusion and discrete cosine transform
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Automatic Target Recognition is one of the most challenging and important requirements in the 21st century battlefield. Developing an algorithm which is complex enough to recognize targets and simple enough to run in real time is a challenging problem. Recognizing different targets with different size, orientation and illumination variations increase the complexity of the problem. This paper proposes a recognition approach, which tries to recognize targets fast and correctly providing robust performance. The proposed algorithm is based on anisotropic diffusion and edge detection for image segmentation and discrete cosine transform (DCT) for image classification. First, difference between target and background is increased by using the anisotropic diffusion filter. In this method, diffusion continues over low contrast pixels, decreasing the difference between smooth regions. On the other hand, diffusion stops over high contrast pixels such that the sharper boundaries are preserved. Anisotropic diffusion method controls the directions of diffusion by an error function which separates low-contrast and high-contrast neighbor pixels. Instead of using partial differential equations or robust statistical equations as an error function, a simple threshold is used to decrease iteration number and operation time. Secondly, possible targets are segmented by using "Canny's edge detection" algorithm and "connected component labeling" algorithm. Finally, possible targets and target database dimensions are reduced and compared by DCT algorithm. In order to minimize the effect of illumination variations, low frequency coefficients aren't used in this comparative study. The proposed algorithm is then tested using example pictures, and is able to find targets in less than a second.
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Nuri Gokhan Korkusuz "High speed automatic target recognition based on anisotropic diffusion and discrete cosine transform", Proc. SPIE 7335, Automatic Target Recognition XIX, 733503 (28 April 2009);

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