Abstract
The aim of this paper is to detect concealed weapons, especially in high security places like in airports, train stations and places with large crowds, where concealed weapons are not allowed. We aim to specify suspicious person who may have a concealed weapon. In this paper, an Image Fusion technique using pixel alignment and discrete wavelet transform is proposed. It is mainly utilized for Concealed Weapon Detection. Image fusion can be defined as extracting information from two or images into a single image to enhance the detection. Image fusion allows detecting concealed weapons underneath a person's clothing with imaging sensors such as Infrared imaging or Passive Millimeter Wave sensors. A data fusion scheme for simpler sensors based on correlation coefficients is proposed and utilized. We proposed an image fusion scheme that utilizes fusion dependency rules using wavelet (WT) and inverse wavelet transform (IWT). The fusion rule is to select the coefficient with the highest correlation rate. The higher the correlation the stronger of the co-existed feature. Experimental results shows the superiority of the proposed algorithm both in quality and real time requirement. The proposed algorithm has a real time response time that is less than other comparable algorithms by 40%. At the same time it retains higher quality as shown in the experimental results. It outperforms other algorithms by superior PSNR of more than 10% of the comparable algorithms in average.