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PROJECT
NAME :
CONCEALED WEAPON DETECTION
CONCEALED WEAPON DETECTION
ABSTRACT
A number of technologies
are being developed for Concealed Weapon
Detection (C WD). Image fusion is studied for detecting weapons or other
objects hidden underneath a person’s clothing. The focus of this project is to
develop a new algorithm to fuse a color visual image and a corresponding IR
image for such a concealed weapon detection application. The fused image
obtained by the proposed algorithm will maintain the high resolution of the
visual image, incorporate any concealed weapons detected by the IR sensor, and
keep the natural color of the visual image. The feasibility of the proposed
fusion technique is demonstrated by some experimental results.
INTRODUCTION
Concealed weapon detection (CWD) is an increasingly
important topic in the general area of law enforcement and it appears to be a
critical technology for dealing with terrorism, which appears to be the most
significant law enforcement problem for the next decade. Existing image sensor
technologies for CWD applications include thermal/infrared (IR), millimeter
wave (MMW), and visual.
Since no single sensor
technology can provide acceptable performance in CWD applications, image fusion
has been identified as a key technology to achieve improved CWD procedures.
Image fusion is a process of combining complementary information from multiple
sensor images to generate a single image that contains a more accurate
description of the scene than any of the individual images. While MMW sensors
have many advantages, the availability of low cost IR technology makes the
study of fusing visual and IR images of great interest.
In our current work, we are interested in using image
fusion to help a human or computer in detecting a concealed weapon using IR and
visual sensors. The visual and IR images have been aligned by image
registration. We observe that the body is brighter than the background in the
IR image. Further the background isalmost black and shows little detail because
of the high thermal emissivity of body. The weapon is darker than the
surrounding body due to a temperature difference between it and the body (it is
colder than human body). The resolution in the visual image is much higher than
that of the IR image, but there is no information on the concealed weapon in
the visual image.
A
variety of image fusion techniques have been developed. They can be
roughly divided into two groups, multi scale
-decomposition-based (MDB) fusion
methods and non-multi scale-decomposition-based (NMDB) fusion methods.
Typical DB fusion methods include
pyramid based methods, discrete wavelet
transform based methods, and discrete
wavelet frame transform based
methods. Typical NMDB methods include
adaptive weight averaging
methods , neural network
based methods , Markov
random field based
methods , and estimation theory
based methods. Most of the image fusion work has been limited to
monochrome images. However, based on
biological research results, the
human visual system is very sensitive to colors. To utilize
this ability, some researchers
map three individual monochrome multispectral images
to the respective
channels of an R
G Bimage to produce a false color fused image. In many cases, this
technique is
applied in combination with another
image fusion procedure. Such a technique
is sometimes called color composite fusion. Another technique is based
on opponent-color processing which maps opponent sensors to human
opponent
colors (red vs. green, blue vs. yellow).
We present a new technique to fuse a color visual image with a
corresponding IR image for a CWD application. Using the proposed method
the
fused image will maintain the high resolution and the natural color of
the
visual image while incorporating any concealed weapons detected by the
IR
sensor.
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