상세 보기
- Lim, Kwangyong;
- Lee, Taewoo;
- Shin, Changmok;
- Chung, Soonwook;
- Choi, Yeongwoo;
- 외 1명
WEB OF SCIENCE
0SCOPUS
6초록
In this paper, we propose a robust illumination system for speed-limit sign recognition in real-time. Real-time traffic sign detection with various illuminations is one of the challenges in a vision-based intelligent vehicle system, as illumination varies greatly in real-world road images based on factors such as driving time, weather, lighting conditions, and driving directions. Our method uses a MCT (Modified Census Transform) as an illumination-invariant method for the real-time detection of traffic signs and uses a SVM (Support Vector Machine) as a classifier for detection and validation. With the proposed method, we have obtained a very high detection rate of 99.8% and recognition rates of 98.4% on various real-world driving images. Copyright 2014 ACM.
키워드
- 제목
- Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines
- 저자
- Lim, Kwangyong; Lee, Taewoo; Shin, Changmok; Chung, Soonwook; Choi, Yeongwoo; Byun, Hyeran
- 발행일
- 2014-01
- 유형
- Conference Paper
- 저널명
- Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014