Real time target identification for security applications
Nowadays, there are a lot of security alarm systems in the markets and those security alarm systems are similar, which is either CCTV video record with alarm siren or security password system with siren, or the combina tion of both. Thus, the real time target identification...
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Main Author: | |
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Format: | Final Year Project Report |
Language: | English English |
Published: |
Universiti Malaysia Sarawak, UNIMAS
2009
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Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/6542/1/REAL%20TIME%20TARGET%20IDENTIFICATION%20FOR%20SECURITY%20APPLICATIONS%2824%20pgs%29.pdf http://ir.unimas.my/id/eprint/6542/8/SALEX%20KUAN.pdf http://ir.unimas.my/id/eprint/6542/ |
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Summary: | Nowadays, there are a lot of security alarm systems
in the markets and those security
alarm systems are similar, which is either CCTV video
record with alarm siren or
security password system with siren, or the combina
tion of both. Thus, the real time
target identification project for the security appl
ications is proposed. In this project,
a real time face detection and face recognition sys
tem for color image sequences is
presented. Basically, the system applies edge detec
tion technique for the face
localization. The system localizes the human head
through outline analysis of
boundaries image, then focusing the attention on a
specific area in the image. The
system applies the same technique to the face recog
nition, with combination of
neural networks. The system extracts the human fac
ial from the color sequences
images and simulates the human facial by using the
neural networks. The simulation
is based on the RGB color layer of images. Neural ne
tworks are used to build the
database of the system for storing the facial image
s and the training data of target
facial. The Rprop technique is used for the trainin
g process for the system. The
system is able to detect the human face and able to
recognize the face. The system
would show the results of target been identified wi
th percentages of matching and
together with the image of the target. The system
can perform well in recognizing
the target and the percentage of matching is above
90%. Besides, the system also
able to recognize the target when the target having
some changes, example like target
wearing hat, veil and etc. The proposed approach i
s using a direct input webcam
video in real time based for the face detection and
face recognition. |
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