Image Based Congestion Detection Algorithms And Its Real Time Implementation
In recent years, intelligent traffic management have included many new fields and features. One of the important fields which directly affect our life is the traffic congestion alert system i.e. a complete system which is able to detect congestion and alert concerned parties to save time, fuel an...
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my-usm-ep.470322021-11-17T03:42:19Z Image Based Congestion Detection Algorithms And Its Real Time Implementation 2015-09-01 Khdiar, Ahmed Nidhal T Technology TK1-9971 Electrical engineering. Electronics. Nuclear engineering In recent years, intelligent traffic management have included many new fields and features. One of the important fields which directly affect our life is the traffic congestion alert system i.e. a complete system which is able to detect congestion and alert concerned parties to save time, fuel and man power. Recent methods in congestion detection need prior knowledge about the road or several minutes are taken to produce results or a huge infrastructure is needed to implement the system, even then, not in real time. Most of the current studies in image processing are not reliable for real implementation because they either lack accuracy or do not work in real time. The proposed system aims to find a new congestion detection method that has high accuracy and having real time processing time, also it aims to demonstrate the transmit/receive process for image transmission using Software Defined Radio. The proposed system offers a complete detection and alert network that captures an image of the road situation, determine whether the road is congested or clear and finally report the results wirelessly to the traffic management bodies to take action and inform people to avoid the congested areas in real time. The proposed system uses a fast and reliable method to detect traffic congestions. The methodology includes vehicle detection by using backlight pairing feature algorithm and modified Watershed algorithm. The results returned by the algorithms are transmitted and received wirelessly using the SFFSDR platform, including the use of RF, FPGA, and DSP modules for variable distances. The system shows an accuracy of detection up to 98-98.8% with time consumption of up to 3 seconds which make it feasible for real time implementation. The wireless system has been tested using different distances between SDR antennas. The received power, bit loss percentage and PSNR for the received image have been obtained, results shows a 35dB PSNR for normal distance between SDR antennas (20cm) and 7dB for 150cm, while bits are totally lost when reaching 200cm. 2015-09 Thesis http://eprints.usm.my/47032/ http://eprints.usm.my/47032/1/Image%20Based%20Congestion%20Detection%20Algorithms%20And%20Its%20Real%20Time%20Implementation.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik & Elektronik |
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Universiti Sains Malaysia |
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USM Institutional Repository |
| language |
English |
| topic |
T Technology T Technology |
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T Technology T Technology Khdiar, Ahmed Nidhal Image Based Congestion Detection Algorithms And Its Real Time Implementation |
| description |
In recent years, intelligent traffic management have included many new fields
and features. One of the important fields which directly affect our life is the traffic
congestion alert system i.e. a complete system which is able to detect congestion and
alert concerned parties to save time, fuel and man power. Recent methods in congestion
detection need prior knowledge about the road or several minutes are taken to produce
results or a huge infrastructure is needed to implement the system, even then, not in real
time. Most of the current studies in image processing are not reliable for real
implementation because they either lack accuracy or do not work in real time. The
proposed system aims to find a new congestion detection method that has high accuracy
and having real time processing time, also it aims to demonstrate the transmit/receive
process for image transmission using Software Defined Radio. The proposed system
offers a complete detection and alert network that captures an image of the road
situation, determine whether the road is congested or clear and finally report the results
wirelessly to the traffic management bodies to take action and inform people to avoid
the congested areas in real time. The proposed system uses a fast and reliable method to
detect traffic congestions. The methodology includes vehicle detection by using
backlight pairing feature algorithm and modified Watershed algorithm. The results
returned by the algorithms are transmitted and received wirelessly using the SFFSDR
platform, including the use of RF, FPGA, and DSP modules for variable distances. The
system shows an accuracy of detection up to 98-98.8% with time consumption of up to 3
seconds which make it feasible for real time implementation. The wireless system has
been tested using different distances between SDR antennas. The received power, bit
loss percentage and PSNR for the received image have been obtained, results shows a
35dB PSNR for normal distance between SDR antennas (20cm) and 7dB for 150cm,
while bits are totally lost when reaching 200cm. |
| format |
Thesis |
| qualification_name |
Doctor of Philosophy (PhD.) |
| qualification_level |
Doctorate |
| author |
Khdiar, Ahmed Nidhal |
| author_facet |
Khdiar, Ahmed Nidhal |
| author_sort |
Khdiar, Ahmed Nidhal |
| title |
Image Based Congestion Detection Algorithms And Its Real Time Implementation |
| title_short |
Image Based Congestion Detection Algorithms And Its Real Time Implementation |
| title_full |
Image Based Congestion Detection Algorithms And Its Real Time Implementation |
| title_fullStr |
Image Based Congestion Detection Algorithms And Its Real Time Implementation |
| title_full_unstemmed |
Image Based Congestion Detection Algorithms And Its Real Time Implementation |
| title_sort |
image based congestion detection algorithms and its real time implementation |
| granting_institution |
Universiti Sains Malaysia |
| granting_department |
Pusat Pengajian Kejuruteraan Elektrik & Elektronik |
| publishDate |
2015 |
| url |
http://eprints.usm.my/47032/1/Image%20Based%20Congestion%20Detection%20Algorithms%20And%20Its%20Real%20Time%20Implementation.pdf |
| _version_ |
1747821749370617856 |