JACIII Vol.10 No.3 pp. 409-418
doi: 10.20965/jaciii.2006.p0409


An Efficient Algorithm for Traffic Sign Detection

Aryuanto Soetedjo*, and Koichi Yamada**

*Information Science and Control Engineering, Nagaoka University of Technology, 1603-1 Kamitomiokamachi, Nagaoka, Niigata 940-2188, Japan

**Management and Information Systems Science, Nagaoka University of Technology, 1603-1 Kamitomiokamachi, Nagaoka, Niigata 940-2188, Japan

July 15, 2005
October 21, 2005
May 20, 2006
traffic sign detection, ellipse detection, geometric fragmentation, genetic algorithm, objective function

We propose an efficient algorithm for detecting traffic signs in images. Geometric fragmentation detects circular red traffic signs in an image by finding and combining the left and right fragments of elliptical objects to increase the accuracy of detection and cope with occlusion. The search for fragments resembles a genetic algorithm (GA) in that it uses the terms individual, population, crossover, and objective function used in the GA. It is different in that it conducts a concurrent random search in a small two-dimensional space devised heuristically. The objective function for evaluating individuals is devised to increase detection accuracy and reduce computation time. The algorithm was tested for detecting circular red traffic signs both from artificial sign images and real scene images. Experimental results demonstrated that the proposed algorithm has higher detection, fewer false alarms, and lower computation cost than GA-based ellipse detection. Compared to conventional template matching, the proposed algorithm performs better in detection and execution time and does not require a large number of carefully prepared templates.

Cite this article as:
Aryuanto Soetedjo and Koichi Yamada, “An Efficient Algorithm for Traffic Sign Detection,” J. Adv. Comput. Intell. Intell. Inform., Vol.10, No.3, pp. 409-418, 2006.
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Last updated on Feb. 25, 2021