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Concealed weapon detection and visualization in a synthesized image

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Abstract

Images acquired by heterogeneous image sensors may provide complementary information about the scene, for instance, the visual image can provide personal identification information like the facial pattern while the infrared (IR) or millimeter wave image can detect the suspicious regions of concealed weapons. Usually, a technique, namely multiresolution pixel-level image fusion is applied to integrate the information from multi-sensor images. However, when the images are significantly different, the performance of the multiresolution fusion algorithms is not always satisfactory. In this study, a new strategy consisting of two steps is proposed. The first step is to use an unsupervised fuzzy k-means clustering to detect the concealed weapon from the IR image. The detected region is embedded in the visual image in the second step and this process is implemented with a multiresolution mosaic technique. Therefore, the synthesized image retains the quality comparable to the visual image while the region of the concealed weapon is highlighted and enhanced. The experimental results indicate the efficiency of the proposed approach.

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Acknowledgements

Mr. D. S. Forsyth is acknowledged for his valuable comments and discussions.

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Authors and Affiliations

  1. School of Information Technology and Engineering Faulty of Engineering, University of Ottawa, SITE-5025, 800 King Edward Ave, P.O. Box 450 STN A, Ottawa, ON, K1N 6N5, Canada

    Zheng Liu & Robert Laganière

  2. Signal Processing and Communications Research Lab, Department of Electrical and Computer Engineering, Lehigh University, 19 Memorial Drive West, Bethlehem, PA, 18015-3084, USA

    Zhiyun Xue & Rick S. Blum

Authors
  1. Zheng Liu
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  2. Zhiyun Xue
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  3. Rick S. Blum
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  4. Robert Laganière
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Correspondence to Zheng Liu.

Additional information

This material is based on part of the work carried out at the SPCR laboratory of Lehigh University and the work is partially supported by the U. S. Army Research Office under grant number DAAD19-00-1-0431. The content of the information does not necessarily reflect the position or the policy of the federal government, and no official endorsement should be inferred.

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Liu, Z., Xue, Z., Blum, R.S. et al. Concealed weapon detection and visualization in a synthesized image. Pattern Anal Applic 8, 375–389 (2006). https://doi.org/10.1007/s10044-005-0020-8

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