Real-time Korean traffic sign detection and recognition

Authors:
Jihie Kim;Kwangyong Lim;YoungJung Uh;SeungGyu Kim;Yeongwoo Choi;Hyeran Byun
Affiliations:
University of Southern California, Marina del Rey, CA;Yonsei University, Seodaemun-Gu, Seoul, Korea;Yonsei University, Seodaemun-Gu, Seoul, Korea;Yonsei University, Seodaemun-Gu, Seoul, Korea;Sookmyung Women's University, Yongsan-Gu, Seoul, Korea;Yonsei University, Seodaemun-Gu, Seoul, Korea
Venue:
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Year:
2013

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Abstract

In this paper, we propose a real-time Korean traffic sign detection and recognition method based on color properties and shape geometries of images. The proposed method supports detecting and recognizing various shapes of traffic signs in real-time. Our method consists of four stages: 1) color based image segmentation; 2) region of interest (ROI) detection; 3) shape classification; and 4) numeral recognition. The proposed method can classify even the signs that are partially occluded. In addition, we improve efficiency of shape classification by using simple shape geometry measurements. Our experiment shows that our approach can provide high classification accuracies for octagonal shape signs (92%) and speed-limit signs (94.5%).