Computer vision based traffic signs recognition system / Edwind Liaw Yee Kang

• Main Author: Edwind , Liaw Yee Kang
• Format: Thesis
• Published: 2017
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://studentsrepo.um.edu.my/8458/4/edwind.pdf; http://studentsrepo.um.edu.my/8458/

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.