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.

Detection method of traffic signs in road scenes

More Information
  • 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
  • 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.

     

  • loading
  • [1]
    王荣本, 赵一兵, 李琳辉, 等. 智能车辆的障碍物检测研究方法综述[J]. 公路交通科技, 2007, 24(11): 109-113. doi: 10.3969/j.issn.1002-0268.2007.11.025

    WANG Rong-ben, ZHAO Yi-bing, LI Lin-hui, et al. Ap-proach reviewof obstacle detection for intelligent vehicle[J]. Journal of Highway and Transportation Research and Deve-lopment, 2007, 24(11): 109-113. (in Chinese) doi: 10.3969/j.issn.1002-0268.2007.11.025
    [2]
    左小清, 李清泉, 谢智颖. 基于车道的道路数据模型[J]. 长安大学学报: 自然科学版, 2004, 24(2): 73-76. https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL200402018.htm

    ZUO Xiao-qing, LI Qing-quan, XIE Zhi-ying. Lane-based road data model[J]. Journal of Chang an University: Natural Science Edition, 2004, 24(2): 73-76. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL200402018.htm
    [3]
    HSUS H, HUANG C L. Road sign detection and recogni-tion using matching pursuit method[J]. I mage and Vision Computing, 2001, 19(3): 119-129. https://www.sciencedirect.com/science/article/pii/S0262885600000500
    [4]
    ARMI NGOL J M, ESCALERA A, HILARIO C, et al. In-telligent vehicle based on visual information[J]. Robotics and Autonomous Systems, 2007, 55(12): 904-916. doi: 10.1016/j.robot.2007.09.004
    [5]
    SOETEDJO A, YAMADA K. Fast and robust traffic sign detection systems[C]∥IEEE. Proceedings of IEEE Interna-tional Conference on Systems, Man and Cybernetics. Waiko-loa: IEEE, 2005: 1341-1346.
    [6]
    MOUTARDE F, BARGETON A, HERBI N A, et al. Ro-bust on-vehicle real-ti me visual detection of American and Eu-ropean speedli mit signs, with a modular traffic signs recogni-tion system[C]∥IEEE. Proceedings of the Intelligent Vehi-cles Symposium. Istanbu: IEEE, 2007: 1122-1126.
    [7]
    初秀民, 严新平, 毛喆. 道路标志自动分类方法[J]. 交通运输工程学报, 2006, 6(4): 91-95. doi: 10.3321/j.issn:1671-1637.2006.04.021

    CHU Xiu-min, YAN Xin-ping, MAO Zhe. Automatic classify method of traffic sign[J]. Journal of Traffic and Transpor-tation Engineering, 2006, 6(4): 91-95. (in Chinese) doi: 10.3321/j.issn:1671-1637.2006.04.021
    [8]
    ESTABLE S, SCHICKJ, STEI N F, et al. Areal-ti me traf-fic sign recognition system[C]∥IEEE. Proceedings of the In-telligent Vehicles Symposium. Paris: IEEE, 1994: 213-218.
    [9]
    冈萨雷斯. 数字图像处理[M]. 第2版. 阮秋琦, 阮宇智, 译. 北京: 电子工业出版社, 2005.
    [10]
    朱双东, 张懿, 陆晓峰. 三角形交通标志的智能检测方法[J]. 中国图象图形学报, 2006, 11(8): 1127-1131. doi: 10.3969/j.issn.1006-8961.2006.08.013

    ZHU Shuang-dong, ZHANG Yi, LU Xiao-feng. Intelligent approach for triangle traffic sign detection[J]. Journal of I mage and Graphics, 2006, 11(8): 1127-1131. (in Chinese) doi: 10.3969/j.issn.1006-8961.2006.08.013
    [11]
    LI U Y X, TAKESHI I, SATOSHI G. A MRF model-based approach to the detection of rectangular shape objectsin color i mages[J]. Signal Processing, 2007, 87(11): 2649-2658. https://www.sciencedirect.com/science/article/pii/S0165168407001715
    [12]
    DAUGMANJ G. High confidence visual recognition of per-sons by a test of statistical independence[J]. IEEE Transac-tions on Pattern Analysis and Machine Intelligence, 1993, 15(11): 1148-1161. doi: 10.1109/34.244676
    [13]
    VEELACERT P. Constructive fitting and extraction of geo-metric pri mitives[J]. Graphical Models and I mage Process-ing, 1995, 9(4): 233-251. https://www.sciencedirect.com/science/article/pii/S1077316997904330
    [14]
    DAVIDE S, STEFANO P, PAOLO V. Ball detection and predictive ball following based on a stereoscopic vision system[C]∥IEEE. International Conference on Robotics and Automation. Barcelona: IEEE, 2005: 1561-1566.
    [15]
    KESODOS A L, PAPAMARKOS N. On the inverse hough transform[J]. Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(12): 1329-1343.
    [16]
    邢军. 基于Sobel算子数字图像的边缘检测[J]. 微机发展, 2005, 15(9): 48-49. https://www.cnki.com.cn/Article/CJFDTOTAL-WJFZ200509016.htm

    XI NG Jun. Edge detection of Sobel-based digital i mage[J]. Microcomputer Development, 2005, 15(9): 48-49. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WJFZ200509016.htm
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (363) PDF downloads(341) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return