Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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An Efficient Signature Recognition Based on Histogram Using Statistical Characteristics

통계적 속성을 이용한 히스토그램 기반 효율적인 서명인식

  • Cho, Yong-Hyun (School of Computer and Information Comm. Eng., Catholic Univ. of Daegu)
  • 조용현 (대구가톨릭대학교 컴퓨터정보통신공학부)
  • Received : 2010.09.06
  • Accepted : 2010.10.07
  • Published : 2010.10.25
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Abstract

This paper presents an efficient signature recognition method by using the hybrid similarity criterion, which is in inverse proportion to distance and in proportion to correlation between the images. The distance is applied to express the spacial property of image, and the correlation is also applied to express the statistical property. The proposed criterion provides the robust recognition to both the geometrical variations such as position, size, and rotation and the shape variation. The normalized cross-correlation(NCC), which is calculated by considering 4 directions based on the histogram of binary image, is applied to express rapidly and accurately the similarity between the images. The proposed method has been applied to the problem for recognizing the 20 truck images of 288*288 pixels and the 105(3 persons * 35 images) signature images of 256*256 pixels, respectively. The experimental results show that the proposed method has a superior recognition performance that appears the image characters well. Especially, the hybrid criterion of NCC and ordinal distance has a superior recognition performance to the hybrid criterion using city-block or Euclidean distance.

본 논문에서는 영상간의 거리에 반비례하고 상관성에 비례하는 조합형 유사성 척도에 의한 효율적인 서명인식 방법을 제안하였다. 여기서 거리는 영상의 공간적 속성을 반영하기 위함이고, 상관성은 통계적 속성을 반영하기 위함이다. 이렇게 하면 서명의 위치, 크기, 회전과 같은 기하학적 변화와 모양변화에 강건한 인식이 가능하다. 상관성의 척도로 이진영상의 히스토그램에 기반을 둔 4 방향의 위치를 고려한 정규상호상관계수를 이용함으로써 서명사이의 유사성을 좀 더 빠르고 정확하게 반영하였다. 제안된 방법을 20개의 288$\times$288 픽셀 트럭영상과 105개의 256$\times$256 픽셀의 서명영상을 대상으로 각각 실험한 결과, 영상의 속성을 잘 반영한 우수한 인식성능이 있음을 확인하였다. 특히 정규상호상관계수와 순서값의 거리를 조합한 척도가 city-block이나 Euclidean 거리를 각각 조합한 척도보다 우수한 인식성능이 있음도 알 수 있었다.

Keywords

References

  1. 김진형, “온라인 서명 검증의 현황 및 방법론 소개,” http:://ai.kaist.ac.kr/~jkim, 2001년 2월
  2. A. A Kholmatov, “Biometric Identity Verification Using On-line & Off-line Signature Verification”, Master of Science Thesis, Sabanci University, Spring 2003.
  3. H. Baltzakis and N. Papamorkos, "A New Signature Verification Technique Based on a Two-stage Neural Network Classifier.", Engineering Application of Intelligence, Vol.14, pp.95-103, Feb. 2001. https://doi.org/10.1016/S0952-1976(00)00064-6
  4. O. Cemil, F. Ercal, and Z. Demir, "Signature Recognition and Verification with ANN” ELECO'03, Dec. 2003.
  5. F. Serratosa and A. Sanfeliu, "Signatures versus Histograms : Definitions, Distances and Algorithms," Pattern Recognition, Vol.39, pp.921-934, May 2006. https://doi.org/10.1016/j.patcog.2005.12.005
  6. F. D. Jou, K. C. Fan, and Y. L. Chang, "Efficient Matching of Large-size Histograms," Pattern Recognition Letters, Vol.25, pp.277-286, Feb. 2004. https://doi.org/10.1016/j.patrec.2003.10.005
  7. S. H. Cha, "Taxonomy of Nominal Type Histogram Distance Measures," American Conference on Applied Mathematics, Harvard, Massachusetts, USA, pp.325-330, Mar. 2008.
  8. T. Kailath, "The Divergence and Bhattacharyya Distance Measures in Signal Selection," IEEE Trans. on Comm. Technology, Vol.15, pp.52-60, Feb. 1967. https://doi.org/10.1109/TCOM.1967.1089532
  9. S. H. Cha and S. N. Srihari, "On Measuring the Distance between Histogram," Pattern Recognition, Vol.35, pp.1355-1370, June 2002. https://doi.org/10.1016/S0031-3203(01)00118-2
  10. X. Yu and M. K. H. Leung, "Shape Recognition using Curve Segment Hausdorff Distance," 18th International Conference on Pattern Recognition. Vol.3, pp.441-444, Aug. 2006.
  11. R. M. Aarts, R. Irwan, and A. J. E. M. Janssen, "Efficient Tracking of the Cross-correlation Coefficient," IEEE. Trans. on Speech Audio Process, Vol. 10, No.6, pp.391-402, Sep. 2002. https://doi.org/10.1109/TSA.2002.803447
  12. F. Zhao, Q. Huang, and W. Gao, "Image Matching by Normalized Cross-Correlation," ICASSP 2006, Vol.2, pp.729-732, May 2006.
  13. T. Ivry, S. Michal, A. Avihoo, G. Sapiro, and D. Barash, "An Image Processing Approach to Computing Distances between RNA Secondary Structures Dot Plots," Algorithms Mol. Biol.. Vol.4, pp.1-19, Feb. 2009. https://doi.org/10.1186/1748-7188-4-1

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