4 August 2009 The study of infrared target recognition at sea background based on visual attention computational model
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Abstract
Infrared images at sea background are notorious for the low signal-to-noise ratio, therefore, the target recognition of infrared image through traditional methods is very difficult. In this paper, we present a novel target recognition method based on the integration of visual attention computational model and conventional approach (selective filtering and segmentation). The two distinct techniques for image processing are combined in a manner to utilize the strengths of both. The visual attention algorithm searches the salient regions automatically, and represented them by a set of winner points, at the same time, demonstrated the salient regions in terms of circles centered at these winner points. This provides a priori knowledge for the filtering and segmentation process. Based on the winner point, we construct a rectangular region to facilitate the filtering and segmentation, then the labeling operation will be added selectively by requirement. Making use of the labeled information, from the final segmentation result we obtain the positional information of the interested region, label the centroid on the corresponding original image, and finish the localization for the target. The cost time does not depend on the size of the image but the salient regions, therefore the consumed time is greatly reduced. The method is used in the recognition of several kinds of real infrared images, and the experimental results reveal the effectiveness of the algorithm presented in this paper.
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Deng-wei Wang, Deng-wei Wang, Tian-xu Zhang, Tian-xu Zhang, Wen-jun Shi, Wen-jun Shi, Long-sheng Wei, Long-sheng Wei, Xiao-ping Wang, Xiao-ping Wang, Guo-qing Ao, Guo-qing Ao, } "The study of infrared target recognition at sea background based on visual attention computational model", Proc. SPIE 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, 73830B (4 August 2009); doi: 10.1117/12.834459; https://doi.org/10.1117/12.834459
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