BOOSTED ROAD SIGN DETECTION AND RECOGNITION

摘要：

This paper presents a boosted system to detect and recognize roads signs from videos. The system first uses the Adaboost algorithm to learn the visual characteristics of road sign. Then, a cascaded structure is then used to detect road signs from videos in real time. After detection, a rectification process is then applied for rectifying different skewed road signs into a normal one. Then, its all embedded texts can be more accurately recognized using their distance maps. On the map, a weighting function is used to balance the importance between a road signs inner and outer feature so that its embedded characters can be more accurately recognized. Experimental results have proved the superiority of the proposed method in road sign recognition.

作者: SIN-YU CHEN JUN-WEI HSIEH

作者单位: Department of Electrical Engineering, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 320, Taiwan

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 3823-3826

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）