Enhancing the seismic histogram equalization of multi-fusion for infrared image of concealed weapon detection
- DOI
- 10.2991/imst-16.2016.23How to use a DOI?
- Keywords
- image enhancement; image seismic; weapon detection; pinpoint area.
- Abstract
The objective of concealed weapon detection is to detect and recognize individuals or groups of terrorists in public areas, such as airports, trains, railways, and even malls. This work investigates how the lives of people in crowded areas can be protected with respect to humanitarian privacy. Seismic histogram equalization is used to enhance captured images and reveal any weapons placed underneath clothes. Infrared images, which have minimum ratios of mistake, are utilized to guarantee safety. This work aims to enhance images obtained by fusion algorithm and use seismic histogram equalization for concealed weapon detection to obtain the needed result in different ways. For images using infrared and color, the mental image (color) only gives the shape of person with color vision. The experimental result of this work clearly the solution of how to detect of concealed weapon underneath person cloths with minimum false and high level of privacy this work relies on infrared images that contain all of the information about weapons carried underneath. The experiment results are based on the enhanced seismic histogram of infrared images.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Nashwan Jasim Hussein AU - Fei Hu AU - Feng He AU - Ayoob Azeez Ayoob PY - 2016/11 DA - 2016/11 TI - Enhancing the seismic histogram equalization of multi-fusion for infrared image of concealed weapon detection BT - Proceedings of the 2016 International Conference on Innovative Material Science and Technology (IMST 2016) PB - Atlantis Press SP - 156 EP - 163 SN - 1951-6851 UR - https://doi.org/10.2991/imst-16.2016.23 DO - 10.2991/imst-16.2016.23 ID - Hussein2016/11 ER -