Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Broken Detection of the Traffic Sign by using the Location Histogram Matching

  • Yang, Liu (Dept. of IT Convergence and Application Engineering, Pukyong National University) ;
  • Lee, Suk-Hwan (Dept. of Information Security, Tongmyong University) ;
  • Kwon, Seong-Geun (Dept. of Electronics Engineering, Kyungil University) ;
  • Moon, Kwang-Seok (Dept. of Electronics Engineering, Pukyong National University) ;
  • Kwon, Ki-Ryong (Dept. of IT Convergence and Application Engineering, Pukyong National University)
  • Received : 2011.09.02
  • Accepted : 2011.12.25
  • Published : 2012.03.31
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Abstract

The paper presents an approach for recognizing the broken area of the traffic signs. The method is based on the Recognition System for Traffic Signs (RSTS). This paper describes an approach to using the location histogram matching for the broken traffic signs recognition, after the general process of the image detection and image categorization. The recognition proceeds by using the SIFT matching to adjust the acquired image to a standard position, then the histogram bin will be compared preprocessed image with reference image, and finally output the location and percents value of the broken area. And between the processing, some preprocessing like the blurring is added in the paper to improve the performance. And after the reorganization, the program can operate with the GPS for traffic signs maintenance. Experimental results verified that our scheme have a relatively high recognition rate and a good performance in general situation.

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References

  1. S.D. zhu, L.L. Liu, and X.F. Lu, "Color-Geometric Model for Traffic Sign Recognition," IMACS Multiconference on CESA, pp. 2028-2032, 2006.
  2. J.H. Lee and K.H. Jo, "Traffic Sign Recognition by Division of Characters and Symbols Regions," Proc. KORUS 2003, Vol.2, pp. 324-328, 2003.
  3. J.D. Jeon, M.J. Lee, J.H. Kim, S.K. Kim, B.D. Kang, "An Object Dection System using Eigen-background and Clustering," Journal of Korea Multimedia Society, Vol.13, No.1, pp.47-57, Jan. 2010. (멀티학회 논문지 추가)
  4. D.G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," ACM Int'I J . Computer Vision, Vol.60, No.2, pp. 91-110, 2004. https://doi.org/10.1023/B:VISI.0000029664.99615.94
  5. D.G. Lowe, "Object Recognition from Local Scale-Invariant Features," Proc. Int'l Conf. Computer Vision (ICCV), pp. 1150-1157, 1999.
  6. F.X. Ren and J.h. Huang, "General Traffic Sign Recognition by Feature Matching," 24th International Conference Image and Vision Computing, pp. 409-414, 2009.
  7. V. Andrey and K.H. Jo, "Automatic Detection and Recognition of Traffic Signs using Geometric Structure Analysis," SICE-ICASE International Joint Conference, pp. 1450-1456, 2006.
  8. M. Teke and A. Temizel, "Multispectral Satellite Image Registration using Scale- Restricted SURF," Pattern Recognition (ICPR), pp. 2310-2313, 2010.
  9. S.L. Huang and C.Cai, "An Efficient Wood Image Retrieval using SURF Descriptor," Test and Measurement ICTM'09, pp. 55-58, 2009.
  10. S.D. Zhu and L.L. Liu, "Traffic Sign Recognition based on Color Standardization," Proc. of the 2006 IEEE International Conference on Information Acquisition, pp. 951-955, 2006.
  11. B.V. Funt and G.D. Finlayson. "Color Constant Color Indexing," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.17, No.5, pp. 522-529, 1995. https://doi.org/10.1109/34.391390
  12. A.E. Johnson and M. Hebert, "Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.21, No.5, pp. 433-449, 1999. https://doi.org/10.1109/34.765655
  13. A. Diplaros and T. Gevers, "Combining Color and Shape Information for Illumination- Viewpoint Invariant object Recognition," IEEE Transactions on Image Processing, Vol.15, No.1, pp. 1-11, 2006. https://doi.org/10.1109/TIP.2005.860320
  14. S. Abbasi and F. Mokhtarian, "Affine-Similar Shape Retrieval: Application to Multiview 3-D Object Recognition," IEEE Transactions on Image Processing, Vol.10, Issue.1, pp. 131-139, 2001. https://doi.org/10.1109/83.892449
  15. C.H. Lai, "An Efficient Real-Time Traffic Sign Recognition System for Intelligent Vehicles with Smart Phones," Technologies and Applications of Artificial Intelligence (TAAI ), pp. 195-202, 2010.
  16. D.M. Tsai, "Independent Component Analysis Based Filter Design for Defect Detection in Low-Contrast Textured Images," Pattern Recognition. ICPR 2006, Vol.2, pp.231-234, 2006.
  17. S. Oprea, "Digital Image Processing Applied in Drugs Industry for Detection of Broken Aspirin Tablets," Electronics Technology. ISSE'08, pp.121-124, 2008.