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Proceedings Paper

Concealed objects detection based on FWT in active millimeter-wave images
Author(s): Kun Du; Lu Zhang; Wei Chen; Guolong Wan; Ruoran Fu
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Paper Abstract

Active millimeter-wave (MMW) near-filed human imaging is a means for concealed objects detection. A method of concealed objects detection based on fast wavelet transforms (FWT) in the usage of active MMW images is presented as a result of image characteristics, which includes high resolution, characteristics varying in different parts of the human, imaging influenced among human, concealed objects and other objects, and different textures of concealed objects. Images segmentation utilizing results of edge detection based on FWT is conducted and preliminary segmentation results can be obtained. Some kinds of concealed objects according to comparing gray value of concealed objects to human average gray value can be detected in this paper. The experiments of concealed objects on images of actual acquisition are conducted with a result of accurate rate 80.92% and false alarm rate 11.78%, illustrating the effectiveness of the method proposed in this paper.

Paper Details

Date Published: 23 January 2017
PDF: 6 pages
Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103221O (23 January 2017); doi: 10.1117/12.2265504
Show Author Affiliations
Kun Du, Beihang Univ. (China)
Lu Zhang, Science and Technology on Metrology and Calibration Lab. (China)
Beijing Institute of Radio Metrology and Measurement (China)
Wei Chen, BeiHang Univ. (China)
Guolong Wan, BeiHang Univ. (China)
Ruoran Fu, BeiHang Univ. (China)

Published in SPIE Proceedings Vol. 10322:
Seventh International Conference on Electronics and Information Engineering
Xiyuan Chen, Editor(s)

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