Browse > Article

Design of a Real-time Algorithm for the Recognition of Speed Limit Signs Using DCT Coefficients  

Kang, Byoung-Hwi (서강대학교 전자공학과 CAD & ES 연구실)
Cho, Han-Min (서강대학교 전자공학과 CAD & ES 연구실)
Kim, Jae-Young (한국전자통신연구원)
Hwang, Sun-Young (서강대학교 전자공학과 CAD & ES 연구실)
Kim, Kwang-Soo (서강대학교 서강미래기술연구원)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.35, no.12B, 2010 , pp. 1766-1774 More about this Journal
Abstract
This paper proposes a real-time algorithm of recognizing speed limit signs for intelligent vehicles. Contrary to previous works which use all the pixel values in the ROI (Region Of Interest) after preprocessing image at ROI and need a lot of operations, the proposed algorithm uses fewer DCT coefficients in the ROI as features of each image to reduce the number of operations. Choosing a portion of DCT coefficients which satisfy discriminant criteria for recognition, the proposed algorithm recognizes the speed limit signs using the information obtained in the selected features through LDA and MD. It selects one having the highest probability among the recognition results calculated by accumulating the classification results of consecutive individual frames. Experimental results show that the recognition rate for consecutive frames reaches to 100% with test images. When compared with the previous algorithm, the numbers of multiply and add operations are reduced by 58.6% and 38.3%, respectively.
Keywords
Intelligent Vehicle; TSR; Speed Limit Signs; DCT; LDA;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 B. Alefs, G. Eschemann, H. Ramoser, and C. Beleznai, "Road Sign Detection from Edge Orientation Histograms", in Proc. IEEE Intelligent Vehicles Symposium, Istanbul, Turkey, pp.993-998, June, 2007.
2 D. Gavrila, "Traffic Sign Recognition Revisited", in Proc. DAGM-Symposium, Bonn, Germany, pp.86-93, Sep., 1999.
3 R. Vicen-Bueno, R. Gil-Pita, M. Rosa-Zurera, M. Utrilla-Manso, and F. Lopez-Ferreras, "Multilayer Perceptrons Applied to Traffic Sign Recognition Tasks", in Proc. International Work-Conference on Artificial Neural Networks, Barcelona, Spain, pp.865-872, June, 2005.
4 S. Hsu and C. Huang, "Road Sign Detection and Recognition Using Matching Pursuit Method", Journal of Image and Vision Computing, Vol.19, No.3, pp.119-129, Feb., 2001.   DOI   ScienceOn
5 P. Douville, "Real-Time Classification of Traffic Signs", Journal of Real-Time Imaging, Vol.6, No.3, pp.185-193, June, 2000.   DOI   ScienceOn
6 Y. Aoyagi and T. Asakura, "A Study on Traffic Sign Recognition in Scene Image Using Genetic Algorithms and Neural Networks", in Proc. IEEE International Conference on Industrial Electronics, Control, and Instrumentation, Taipei, Vol.3, pp.1838-1843, Aug., 1996.
7 S. Maldonado-Bascon, S. Lafuente-Arroyo, P. Gil-Jimenez, H. Gomez-Moreno, and F. Lopez -Ferreras, "Road-Sign Detection and Recognition Based on Support Vector Machines", IEEE Trans. on Intelligent Transportation Systems, Vol.8, No.2, pp.264-278, June, 2007.   DOI
8 A. de la Escalera, J. Armingol, J. Pastor, and F. Rodriguez, "Visual Sign Information Extraction and Identification by Deformable Models for Intelligent Vehicles", IEEE Trans. on Intelligent Transportation Systems, Vol.5, No.2, pp.57-68, June, 2004.   DOI   ScienceOn
9 X. Baro, S. Escalera, J. Vitria, O. Pujol, and P. Radeva, "Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification", IEEE Trans. on Intelligent Transportation Systems, Vol.10, No.1, pp.113-126, Mar., 2009.   DOI   ScienceOn
10 P. Viola and M. Jones, "Robust Real-time Face Detection", International Journal of Computer Vision, Vol.57, No.2, pp.137-154, May, 2004.   DOI
11 P. Paclik, J. Novovicova, P. Pudil, and P. Somol, "Road Sign Classification Using the Laplace Kernel Classifier", Pattern Recognition Letter, Vol.21, No.13/14, pp.1165-1173, Dec., 2000.   DOI   ScienceOn
12 G. Hughes, "On the Mean Accuracy of Statistical Pattern Recognizers", IEEE Trans. on Information Theory, Vol.14, No.1, pp.55-63, Jan., 1968.   DOI
13 A. Martinez and A. Kak, "PCA versus LDA", IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.23, No.2, pp.228-233, Feb., 2001.   DOI   ScienceOn
14 Open Computer Vision Library, http://opencvlibrary.sourceforge.net.
15 오준택, 곽현욱, 김욱현, "웨이블릿 변환과 형태 정보를 이용한 교통 표지판 인식", 대한전자공학회논문지, 41권 5호, pp.125-134, 2004년 9월.   과학기술학회마을
16 김상환, 김진화, 김창수, "지능형 자동차를 위한 컴퓨터 비전 기술 동향", 대한전자공학회지, 37권 5호, pp.59-71, 2010년 5월.
17 C. Bahlmann, Y. Zhu, R. Visvanathan, M. Pellkofer, and T. Koehler, "A System for Traffic Sign Detection, Tracking, and Recognition Using Color, Shape, and Motion Information", in Proc. IEEE Intelligent Vehicles Symposium, Las Vegas, NV, pp.255- 260, June, 2005.
18 C. Keller, C. Sprunk, C. Bahlmann, J. Giebel, and G. Baratoff, "Real-time Recognition of U.S. Speed Signs", in Proc. IEEE Intelligent Vehicles Symposium, Eindhoven, Netherland, pp.518-523, June, 2008.
19 X. Gao, L. Podladchikova, D. Shaposhnikov, K. Hong, and N. Shevtsova, "Recognition of Traffic Signs Based on their Colour and Shape Features Extracted Using Human Vision Models", Journal of Visual communication and Image Representation, Vol.17, No.4, pp.675-685, Aug., 2006.   DOI   ScienceOn
20 Y. Damavandi and K. Mohammadi, "Speed Limit Traffic Sign Detection and Recognition", in Proc. IEEE Cybernetics and Intelligent Systems, Singapore, Vol.2, pp.213-218, Dec., 2004.
21 H. Shen and X. Tang, "Generic Sign Board Detection in Images", in Proc. ACM SIGMM international workshop on Multimedia information retrieval, Berkeley, CA, pp.144-149, Nov., 2003.