Detection method of traffic signs in road scenes

ZHANG Ning; HE Tie-jun; GAO Chao-hui; HUANG Wei

Volume 8 Issue 6

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ZHANG Ning, HE Tie-jun, GAO Chao-hui, HUANG Wei. Detection method of traffic signs in road scenes[J]. Journal of Traffic and Transportation Engineering, 2008, 8(6): 104-109.

Citation:

ZHANG Ning, HE Tie-jun, GAO Chao-hui, HUANG Wei. Detection method of traffic signs in road scenes[J]. Journal of Traffic and Transportation Engineering, 2008, 8(6): 104-109.

ZHANG Ning, HE Tie-jun, GAO Chao-hui, HUANG Wei. Detection method of traffic signs in road scenes[J]. Journal of Traffic and Transportation Engineering, 2008, 8(6): 104-109.

Citation:

ZHANG Ning, HE Tie-jun, GAO Chao-hui, HUANG Wei. Detection method of traffic signs in road scenes[J]. Journal of Traffic and Transportation Engineering, 2008, 8(6): 104-109.

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Detection method of traffic signs in road scenes

ITS Research Center, Southeast University, Nanjing 210096, Jiangsu, China

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Author Bio:
ZHANG Ning (1972-), male, associate professor, PhD, +86-25-83793131, ningzhang1972@yahoo.com.cn
Received Date: 2008-07-12
Publish Date: 2008-12-25

Abstract

Abstract

In order to quickly identify traffic signs in road scenes with vehicle visual navigation, a detection method was put forward by extracting the color characteristics of traffic signs and recognizing the shape characteristics of targets. The road scene image of RGB space was transformed into that of HSI space, a syncretic method of hue and saturation was used to extract the characteristic color area of sign in road scene, then traffic sign image was binarized, the noise was removed, and binarization target was projected to locate traffic sign. A red circular interdictory traffic sign was taken as example, and an improved Hough transform method was proposed to recognize the geometrics of the sign area. Analysis result shows that after 20 road scene tests, including interdictory traffic signs under different conditions, the detection rates of color area locations and geometric characteristics recognitions for traffic signs reach 100%, and the average detection time is 245 ms, so the method not only locates the sign area quickly and correctly, but also recognizes the geometric graph of interdictory traffic sign with real-time property and robustness.
- traffic information engineering,
- traffic sign detection,
- HSI space,
- improved Hough transformation

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References(16)

References

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