Traffic intensity monitoring using multiple object detection with traffic surveillance camera /

Roads in Malaysia are getting more congested every day and the problem does not seem to have a solution. Many researches are done to reduce the traffic congestion however there are no practical or real-time solution to the problem. Most researches are only able to simulate the traffic or rather gene...

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Bibliographic Details
Main Author: Muhammad Hamdan bin Hasan Gani (Author)
Format: Thesis
Language:English
Published: Kuala Lumpur : Kuliyyah of Engineering, International Islamic University Malaysia, 2018
Subjects:
Online Access:Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library.
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100 0 |a Muhammad Hamdan bin Hasan Gani,  |e author 
245 1 0 |a Traffic intensity monitoring using multiple object detection with traffic surveillance camera /  |c by Muhammad Hamdan bin Hasan Gani 
264 1 |a Kuala Lumpur :  |b Kuliyyah of Engineering, International Islamic University Malaysia,  |c 2018 
300 |a xiii, 67 leaves :  |b illustrations ;  |c 30cm. 
336 |2 rdacontent  |a text 
347 |2 rdaft  |a text file  |b PDF 
502 |a Thesis (MSCIE)--International Islamic University Malaysia, 2018. 
504 |a Includes bibliographical references (leaves 63-66). 
520 |a Roads in Malaysia are getting more congested every day and the problem does not seem to have a solution. Many researches are done to reduce the traffic congestion however there are no practical or real-time solution to the problem. Most researches are only able to simulate the traffic or rather generalize the pattern into simpler arrival models, however this will not reflect on the actual road conditions. In this research, an alternative approach to measure the traffic intensity on the road is discussed. With computer vision has become a key business element in many corporations and the rise in the technology of cameras with lower costs of processing has enabled us to develop on most advanced system for many applications. Using traffic surveillance camera placed on roads and object detection algorithm, a new method of calculating the traffic intensity is developed and tested. Results of the test show the accuracy of about 80% for the algorithm to be able to tell the difference between number of cars and motorcycles. With this information, the road condition is estimated with higher accuracy. The result and performance are tabulated and some of the limitations are discussed in detail in the last chapter. However, there is still a lot of work need to be done until the application can run accurately in real-time. 
596 |a 1 
655 7 |a Theses, IIUM local 
690 |a Dissertations, Academic  |x Department of Electrical and Computer Engineering  |z IIUM 
710 2 |a International Islamic University Malaysia.  |b Department of Electrical and Computer Engineering 
856 4 |u http://studentrepo.iium.edu.my/handle/123456789/5310  |z Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library. 
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