Browse > Article
http://dx.doi.org/10.5302/J.ICROS.2011.17.5.479

Vehicle Identification Number Recognition using Edge Projection and PCA  

Ahn, In-Mo (Masan College)
Ha, Jong-Eun (Seoul National University of Science and Technology)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.17, no.5, 2011 , pp. 479-483 More about this Journal
Abstract
The automation of production process is actively expanding for the purpose of the cost reduction and quality assurance. Among these, automatic tracking of the product along the whole process of the production is also important topic. Typically this is done by adopting OCR technology. Conventional OCR technology operates well on the rather good quality of the image like as printed characters on the paper. In industrial application, IDs are marked on the metal surface, and this cause the height difference between background material and character. Illumination systems that guarantee an image with good quality may be a solution, but it is rather difficult to design such an illumination system. This paper proposes an algorithm for the recognition of vehicle's ID characters using edge projection and PCA (Principal Component Analysis). Proposed algorithm robustly operates under illumination change using the same parameters. Experimental results show the feasibility of the proposed algorithm.
Keywords
OCR; segmentation; vehicle ID;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
Times Cited By SCOPUS : 0
연도 인용수 순위
1 www.cognex.com.
2 S. Mori, C. Y. Suen, and K. Yamamoto, "Historical review of OCR research and development," Proc. of the IEEE, vol. 80, no. 7, pp. 1029-1058, 1992.   DOI
3 R. Plamondon and S. N. Srihari, "Online and off-line handwriting recognition: a comprehensive survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 63-84, 2000.   DOI
4 J. E. Ha, D. J. Kang, M. H. Jeong, and W. H. Lee, "Robust segmentation of characters marked on surface," LNCIS 345, pp. 478-487, 2006.
5 www.matrox.com.
6 S. Kanhan, T. Pavlidis, and H. S. Baird, "On the recognition of printed characters of any font and size," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 9, no. 2, pp. 274-288, 1978.   DOI
7 S. W. Lee, D. J. Lee, and H. S. Park, "A new methodology for gray-scale character segmentation and recognition," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 18, no. 10, pp. 1045-1050, 1996.   DOI
8 T. Sato, M. Smith, S. Satoh, T. Kanade, and E. Hughes, "Video OCR: indexing digital news libraries by recognition of superimposed caption," ACM Multimedia Systems Special Issue on Video Libraries, vol. 7, no. 5, pp. 385-395, 1999.
9 S. S. Kim, H. K. Kwag, and S. H. Kim, "A survey on the research of optical font recognition," University Journal of Chonnam, vol. 5, no. 1, pp. 1-16, 2001.
10 J. H. Jung and J. H. Park, "A PCB character recognition system using rotation-invariant features," Journal of Control, Automation, and Systems Engineering(in Korean), vol. 12, no. 3, pp. 241-247, Mar. 2006.   과학기술학회마을   DOI
11 G. Baptista and K. M. Kulkami, "A high accuracy algorithm for recognition of handwritten numerals," Pattern Recognition, vol. 21, no. 4, pp. 287-291, 1988.   DOI
12 S. H. Kim, S. W. Jeong, and I. S. Oh, "A survey on the off-line recognition of handwritten korean characters," Proc. of KIISE (Korean Institute of Information Scientists and Engineers), pp. 396-398, 1998.
13 L. Yi, "Machine printed character segmentation - an overview," Pattern Recognition, vol. 28, no. 1, pp. 67-80, 1995.   DOI