Abstract
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.
| Original language | English |
|---|---|
| DOIs | |
| Publication status | Published - 2014 Jan 1 |
| Event | 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014 - Siem Reap, Cambodia Duration: 2014 Jan 9 → 2014 Jan 11 |
Other
| Other | 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014 |
|---|---|
| Country | Cambodia |
| City | Siem Reap |
| Period | 14/1/9 → 14/1/11 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Information Systems
Cite this
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Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines. / Lim, Kwangyong; Lee, Taewoo; Shin, Changmok; Chung, Soonwook; Choi, Yeongwoo; Byun, Hyeran.
2014. Paper presented at 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014, Siem Reap, Cambodia.Research output: Contribution to conference › Paper
TY - CONF
T1 - Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines
AU - Lim, Kwangyong
AU - Lee, Taewoo
AU - Shin, Changmok
AU - Chung, Soonwook
AU - Choi, Yeongwoo
AU - Byun, Hyeran
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84899707632&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84899707632&partnerID=8YFLogxK
U2 - 10.1145/2557977.2558090
DO - 10.1145/2557977.2558090
M3 - Paper
ER -