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Imaging for Concealed Weapon Detection

Published on September 2015 by Sadanand M Hegde, Neha N, Shivaprasad K
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National Conference “Electronics, Signals, Communication and Optimization"
Foundation of Computer Science USA
NCESCO2015 - Number 4
September 2015
Authors: Sadanand M Hegde, Neha N, Shivaprasad K
dfc7b507-9477-445b-8a5b-295397ec6fc4

Sadanand M Hegde, Neha N, Shivaprasad K . Imaging for Concealed Weapon Detection. National Conference “Electronics, Signals, Communication and Optimization". NCESCO2015, 4 (September 2015), 5-9.

@article{
author = { Sadanand M Hegde, Neha N, Shivaprasad K },
title = { Imaging for Concealed Weapon Detection },
journal = { National Conference “Electronics, Signals, Communication and Optimization" },
issue_date = { September 2015 },
volume = { NCESCO2015 },
number = { 4 },
month = { September },
year = { 2015 },
issn = 0975-8887,
pages = { 5-9 },
numpages = 5,
url = { /proceedings/ncesco2015/number4/22314-5335/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference “Electronics, Signals, Communication and Optimization"
%A Sadanand M Hegde
%A Neha N
%A Shivaprasad K
%T Imaging for Concealed Weapon Detection
%J National Conference “Electronics, Signals, Communication and Optimization"
%@ 0975-8887
%V NCESCO2015
%N 4
%P 5-9
%D 2015
%I International Journal of Computer Applications
Abstract

In today's world, security forms an integral part in every aspect of life. The detection of weapons concealed underneath a person's clothing is very much important to the improvement of the security of the general public as well as the safety of public assets like airports, building and railway stations, etc. Manual screening procedures for detecting concealed weapons are common in controlled access settings like airports, entrance to sensitive buildings and public events. It is desirable sometimes to be able to detect concealed weapons from a standoff distance, especially when it is impossible to arrange the flow of people through a controlled procedure. In this project we propose an automated weapon detection using millimeter wave imagining method. The millimeter wave scans the entire body, without causing any side-effects, for concealed weapon. We enhance the millimeter wave image and follow it up with segmentation. The system has built-in intelligence to detect the concealed weapon after segmentation. We also use wavelet based fusing techniques to pin-point the position of the concealed weapon

References
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  5. http://www. academia. edu/2704626/compressive_sampling_with_unknown_blurring_function_application_to_passive_millimeter-wave_imaging
  6. http://eeweb. poly. edu/iselesni/DoubleSoftware/dintro. html
  7. D. L. Donoho,"De-Noising by Soft Thresholding", IEEE Trans. Info. Theory 43, pp. 933-936, 1993
  8. Nobuyuki Otsu, "A Threshold Selection Method from Gray-Level Histograms", IEEE Tx on SMC, Vol. 9, No. 1, Jan 1979, pp 62-66.
Index Terms

Computer Science
Information Sciences

Keywords

Detection Wavelets Image Segmentations Fusion Image Denoising