Development of video image acquisition for traffic surveillance using open source software
The Research works to presents an innovative approach in monitoring system by applying new programming methods which can be used for Traffic/Road Surveillance Systems. Nowadays, the development of traffic surveillance on the road is compulsory as highways and roads are getting crowded especially...
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| Format: | Thesis |
| Language: | English |
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| Online Access: | http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31924/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31924/2/Full%20text.pdf |
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| Summary: | The Research works to presents an innovative approach in monitoring system by
applying new programming methods which can be used for Traffic/Road Surveillance
Systems. Nowadays, the development of traffic surveillance on the road is compulsory
as highways and roads are getting crowded especially in the cities. These crowded
situations would increase the number of accidents on the roads. The Traffic
Surveillance System performs image recognition and object tracking processing. A
camera is used to monitor specific roads (highways, motorways, junctions…etc) and
communicate with the main server. The main server integrates the target image from
the camera after processing it in several steps then communicates with another
computer by sending the image to it. A prototype implementation of traffic surveillance
is based on OpenCV programming under GNU-Linux supported by socket
programming. The objectives of traffic surveillance system are tracking moving
vehicles, counting them and detecting the abnormal movement in specific places. This is
done by analyzing the frames captured and processing them using OpenCV functions.
The use of open source resources such as OpenCV functions in GNU- Linux provides an
easy method to use the computer vision framework besides it can run vision code in real
time. The traffic surveillance works in real-time process for (5-33 fps) of video stream
in a rainy day and a sunny day. Traffic surveillance system accepts video images either
from the camera captures or from the files. It tracks the moving vehicles using image
processing and recognition algorithms such as converting to Gray scale and Mixture of
Gaussian method; it marks each moving vehicle with a rectangle box and counts them.
The system consists of: capturing part, tracking part, detecting abnormal movement
from specific points and streaming the view to the other connecting computer. Besides it
could minimize the frame processing in the case of the frame capture with high
resolution. The system has successfully been tested in three different processor speeds
which are 1.2 GHz CPU, 2.0 GHz CPU and 2.6 GHz CPU. The results are quite
accurate and are measured in mille second. The system works in outdoor environment
which is complex with wavering tree branches and flow of rain. Besides it updates
frame by frame in any module of background views especially from the upper view of
the road in order to get a significant images of all the objects. The results could be
recorded by saving the requested group of photos in any image format. The CPU
processing speed with the frame size process represents one of the key factors of the
performance analysis of traffic surveillance. Processing speed comparison of the
processing steps results in different resolutions for frame size made. And, a significant
result is found by reducing the calculation time of processing when the frames size
captured are reduced. The experiment was done by using 9 different views each with
700 frames consist of different views of moving vehicles in sunny or rainy situations on
the roads of Perlis state. These experiments successfully detected the movements of all
types of vehicles. |
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