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Automatic vehicle recognition in multiple cameras for video surveillance

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Abstract

To efficiently locate identical objects in heterogeneous cameras and possibly propagate reliable information between cameras and refine detection, many techniques were used to recognize vehicles. In this paper, we investigate several key problems and present a novel approach for automatic vehicle recognition (AVR) in multiple cameras for video surveillance application. We propose a level-based region comparison algorithm to AVR in multiple cameras. For improving the recognition accuracy, new license plate recognition method is also proposed. Experimental results show that the proposed algorithm is simple and efficient, and the quality of the composed image can be comparable with the results of the state-of-the-art methods.

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Acknowledgments

The authors would like to thank the anonymous reviewers for their helpful comments. This work is partly supported by National Science Foundation of China (Grant No.61300092).

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  1. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan , 610054, China

    Yunbo Rao

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  1. Yunbo Rao
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Correspondence to Yunbo Rao.

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Rao, Y. Automatic vehicle recognition in multiple cameras for video surveillance. Vis Comput 31, 271–280 (2015). https://doi.org/10.1007/s00371-013-0917-y

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