A real-time traffic sign recognition system based on local structure features

Kwangyong Lim, Hyeran Byun, Yeongwoo Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present an accurate and efficient system for traffic sign recognition in a real-world driving scene video. The proposed system uses local structure features to achieve high, illumination-invariant accuracy in detection and recognition. We exploit a property of traffic signs, namely, shared boundary shapes, to enhance the speed and accuracy of the detection step. A multi-level SVM structure is employed for stable recognition. The proposed method can process real-world road driving scene video in real time with high accuracy, over 98%, in both detection and recognition.

Original languageEnglish
Title of host publicationProceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015
EditorsHamid R. Arabnia, Leonidas Deligiannidis, Fernando G. Tinetti, George Jandieri, Gerald Schaefer, Ashu M. G. Solo
PublisherCSREA Press
Pages65-68
Number of pages4
ISBN (Electronic)1601324049, 9781601324047
Publication statusPublished - 2015 Jan 1
Event2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015, at WORLDCOMP 2015 - Las Vegas, United States
Duration: 2015 Jul 272015 Jul 30

Publication series

NameProceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015

Conference

Conference2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015, at WORLDCOMP 2015
CountryUnited States
CityLas Vegas
Period15/7/2715/7/30

Fingerprint

Traffic signs
Lighting

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

Cite this

Lim, K., Byun, H., & Choi, Y. (2015). A real-time traffic sign recognition system based on local structure features. In H. R. Arabnia, L. Deligiannidis, F. G. Tinetti, G. Jandieri, G. Schaefer, & A. M. G. Solo (Eds.), Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015 (pp. 65-68). (Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015). CSREA Press.
Lim, Kwangyong ; Byun, Hyeran ; Choi, Yeongwoo. / A real-time traffic sign recognition system based on local structure features. Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015. editor / Hamid R. Arabnia ; Leonidas Deligiannidis ; Fernando G. Tinetti ; George Jandieri ; Gerald Schaefer ; Ashu M. G. Solo. CSREA Press, 2015. pp. 65-68 (Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015).
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Lim, K, Byun, H & Choi, Y 2015, A real-time traffic sign recognition system based on local structure features. in HR Arabnia, L Deligiannidis, FG Tinetti, G Jandieri, G Schaefer & AMG Solo (eds), Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015. Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015, CSREA Press, pp. 65-68, 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015, at WORLDCOMP 2015, Las Vegas, United States, 15/7/27.

A real-time traffic sign recognition system based on local structure features. / Lim, Kwangyong; Byun, Hyeran; Choi, Yeongwoo.

Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015. ed. / Hamid R. Arabnia; Leonidas Deligiannidis; Fernando G. Tinetti; George Jandieri; Gerald Schaefer; Ashu M. G. Solo. CSREA Press, 2015. p. 65-68 (Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Lim K, Byun H, Choi Y. A real-time traffic sign recognition system based on local structure features. In Arabnia HR, Deligiannidis L, Tinetti FG, Jandieri G, Schaefer G, Solo AMG, editors, Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015. CSREA Press. 2015. p. 65-68. (Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015).