Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines

Kwangyong Lim; Taewoo Lee; Changmok Shin; Soonwook Chung; Yeongwoo Choi; Hyeran Byun

doi:10.1145/2557977.2558090

Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines

Kwangyong Lim, Taewoo Lee, Changmok Shin, Soonwook Chung, Yeongwoo Choi, Hyeran Byun

Department of Computer Science

Research output: Contribution to conference › Paper › peer-review

3 Citations (Scopus)

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	https://doi.org/10.1145/2557977.2558090
Publication status	Published - 2014
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

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Information Systems

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Lim, K., Lee, T., Shin, C., Chung, S., Choi, Y., & Byun, H. (2014). Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines. Paper presented at 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014, Siem Reap, Cambodia. https://doi.org/10.1145/2557977.2558090

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title = "Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines",

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.",

author = "Kwangyong Lim and Taewoo Lee and Changmok Shin and Soonwook Chung and Yeongwoo Choi and Hyeran Byun",

year = "2014",

doi = "10.1145/2557977.2558090",

language = "English",

note = "8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014 ; Conference date: 09-01-2014 Through 11-01-2014",

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Lim, K, Lee, T, Shin, C, Chung, S, Choi, Y & Byun, H 2014, 'Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines', Paper presented at 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014, Siem Reap, Cambodia, 14/1/9 - 14/1/11. https://doi.org/10.1145/2557977.2558090

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 › peer-review

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

Y1 - 2014

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.

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M3 - Paper

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T2 - 8th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2014

Y2 - 9 January 2014 through 11 January 2014

ER -

Real-time illumination-invariant speed-limit sign recognition based on a modified census transform and Support Vector Machines

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