Edwind , Liaw Yee Kang (2017) Computer vision based traffic signs recognition system / Edwind Liaw Yee Kang. Masters thesis, University of Malaya.
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Abstract
Nowadays, the number of moving vehicles and road users have been increasing very rapidly. Subsequently, more road safety issues have been raised up. Traffic signs on road play a very big role for road safety because it carries important message for the road users especially the drivers. Hence, it is essential that the drivers can notice the traffic signs so that appropriate decision and response during can be made. However, the chances of the drivers overlook some signs are still very high. In order to minimize the said chances, a computer vision based traffic signs detection and recognition system is proposed and developed. The machine learning algorithm, cascaded classifier based on Haar-like features is adopted to develop the traffic signs detection and recognition system. By adopting Haar-like features cascaded classifiers, the traffic signs detection and recognition system with high accuracy is developed.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | Research Report (M.A.) - Faculty of Engineering, University of Malaya, 2017. |
| Uncontrolled Keywords: | Computer; Detection; Recognition system; Cascaded |
| Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Engineering |
| Depositing User: | Mr Prabhakaran Balachandran |
| Date Deposited: | 24 Jul 2019 04:05 |
| Last Modified: | 11 Feb 2020 04:03 |
| URI: | http://studentsrepo.um.edu.my/id/eprint/8458 |
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