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http://dx.doi.org/10.7319/kogsis.2013.21.3.019

Automatic Measurement Method of Traffic Signs Using Image Recognition and Photogrammetry Technology  

Chang, Sang Kyu (Dept. of Civil Engineering, Kyungpook National University)
Kim, Jin Soo (Dept. of Construction Information, Andong Science College)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.21, no.3, 2013 , pp. 19-25 More about this Journal
Abstract
Recently, more accurate database information of facilities is being required, with the increase in importance of urban road facility management. Therefore, this study proposed how to automatically detect particular traffic signs necessary for efficient construction of road facility DB. For this study, central locations of facilities were searched, after recognition and automatic detection of particular traffic signs through an image. Then, coordinate values of traffic signs calculated in the study were compared with real coordinate values, in order to evaluate the accuracy of traffic sign locations which were finally detected. Computer vision technology was used in recognizing and detecting traffic signs through OPEN CV-based coding, and photogrammetry was used in calculating accurate locations of detected traffic signs. For the experiment, circular road signal(No Parking) and triangular road signal(Crosswalk) were chosen out of various kinds of road signals. The research result showed that the circular road signal had a nearly 50cm error value, and the triangular road signal had a nearly 60cm error value, when comparing the calculated coordinates with the real coordinates. Though this result is not satisfactory, it is considered that there would be no problem to find locations of traffic signs.
Keywords
Automatic Detection; Computer Vision; OPEN CV; Photogrammetry; Collinearity Condition;
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Times Cited By KSCI : 4  (Citation Analysis)
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1 Jeong, D. H., Kim, B. K. and Kim, J. H., 2002, Development of car MMS S/W for road facilities DB construction, Korea Spatial Information Society. Proceedings of the '2002 Autumn Meeting, pp.89-93.
2 Kim, D. H., Im J. H., Kim, D. H., Kim T. K. and Paik, J. K., 2009, Face detection and tracking using skin color information and Haar-like features in real-time video, Korean HCI Society, HCI 2009 Congress, pp.146-149.   과학기술학회마을
3 Min, J. H., Lee, W. C. and Hong, K. C., 2004, Face detection ＆ amp; Identification system using Haar-like feature/HMM, Korean Institute of Information Scientists and Engineers, Proceedings of the 2004 Autumn Meeting, Vol.31, No.2, pp. 739-741.   과학기술학회마을
4 Paul R. Wolf and Bon A. Dewitt, 2000, Elements of photogrammetry : with application in GIS. McGraw- Hill Inc.
5 Park, S. H., Cho, D. H. and Park, K. R., 2008, A study on eye detection using AdaBoost for iris recognition in mobile environments, The Institute of Electronics Engineers of Korea, Vol.45 CI No.4, pp.1-11.   과학기술학회마을
6 Park, C. H. and Namkung, J. C., 2005, Comparison of recognition rate with distance on stereo face images base PCA, Journal of Semiconductor Technology and Science, Vol.42, SP-1-1, pp.9-16.   과학기술학회마을
7 R. Lienhart and A. Wemicke, 2002, Localizing and segmenting text in images and videos, IEEE Trans. Circuits Syst. Video Technol, Vol.12, No.4, pp. 256-269.   DOI   ScienceOn
8 Asakura, T. and Aoyagi, Y., 1994, Image recognition of traffic speed marks using neural networks, JSME Trans., Vol.61, No.589, pp.206-212.
9 Auranuch Lorsakul and Jackrit Suthakorn, 2007, Traffic sign recognition for intelligent vehicle/driver assistance system using neural network on OpenCV, the 4th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI 2007).
10 C. Kotropoulos and I. Pitas, 1997, Rule-based face detection in frontal views, Proc Int'l Conf. Acoustics, Signal Processing, Vol.4, pp.2537-3541.
11 Yoon, C. Y., Jang, S. Y. and Park, M. G., 2009, Real-time road sign detection using vertical plane and AdaBoost, The Institute of Electronics Engineers of Korea, Vol.46, SC-5-5, pp.29-37.   과학기술학회마을
12 Shin, M. C., 2006, Traffic sign recognition using color information and neural networks, Master's thesis, Inha University.
13 Viola, P., and Jones, M., 2001, Rapid object detection using a Boosted cascade of simple features, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol.1, pp.511-518.
14 Yoo, B. et. al., 2000, The Development of real-time photogrammetric system using digital photogrammetry and GPS, Korea Institute of Construction Technology.
15 Jeong, M. H., 2000, Blunder detection by matching strength measurement in digital photogrammetry, Master's thesis, Sungkyunkwan University.
16 Samaria, F., 1994, Face recognition using hidden markov models, Ph.D. dissertation, University of Cambridge.
17 Choi, M. S., Lee, J. H., Suk, J. H., Roh, T. M. and Shim, J. C., 2010, Vehicle detection based on the Haar-like feature and image segmentation, Journal of Korea Multimedia Society, Vol.13, No.9, pp.1314-1321.   과학기술학회마을
18 Di Zenzo, S., 1986, A note on the gradient of a multi image, Vol.33, pp.116-125.   DOI   ScienceOn