An Alternative Method to Discover Concealed Weapon Detection Using Critical Fusion Image of Color Image and Infrared Image

被引:0
作者
Hussein, Nashwan Jasim [1 ]
Hu, Fei [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan, Peoples R China
来源
2016 FIRST IEEE INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND THE INTERNET (ICCCI 2016) | 2016年
关键词
DWT; HSV image; image fusion; weapon detection; infrared image;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The terrorist attacks are major concerns to many countries all over the world therefore most of countries are working on researches over different security techniques to predict the possibilities of such terrorist attacks before its happening for saving the number of human lives and important assets. Video processing and image processing security methods presented by researchers in order to detect the explosive resources or weapon carrying by group humans or individuals However most of methods of literature suffered from the accuracy and robustness issue The most interesting research is accurate method of weapon detection using image processing methods. Since from last decade many image processing based methods proposed for improving and detecting the hidden weapons inside the cloths. The methods like fusion, enhancement, tracking, registration as well as recognition are evaluated successfully. However existing methods still required being efficient in terms of time accuracy and computational overhead in this paper it is presenting the new framework for robust detection weapons hidden in clothes by using color image and infrared image as input and then applying process of image fusion with discrete wavelet transform analysis and segmentation using thresholding method. The infrared (IR) image is used as it helps to get visual information about hidden weapons. The experimental results introduced in this paper are prepared by using real time RBG and IR images those are captured by infrared sensors. This paper introduced the detailed procedure, algorithms and systematic framework of automatic weapon detection approach.
引用
收藏
页码:378 / 383
页数:6
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