Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Shape Image Recognition by Using Histogram-based Correlation

히스토그램 기반 상관성을 이용한 모양영상 인식

  • Cho, Yong-Hyun (School of Computer and Information Comm. Eng., Catholic Univ. of Daegu)
  • 조용현 (대구가톨릭대학교 컴퓨터정보통신공학부)
  • Received : 2010.05.12
  • Accepted : 2010.07.29
  • Published : 2010.08.25
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Abstract

This paper presents an effective shape image recognition method using the correlation based on 4-dimensional histogram. The histogram-based correlation is accurately applied to express the similarity by comparing the positions of a corresponding dimension between the images, which is calculated by considering 4 directions of the shape image. The correlation measure by using the normalized cross-correlation is also applied to obtain the robust recognition to the geometrical variations such as shape, position, size, and rotation. The proposed method has been applied to the problem for recognizing the 8 shape images of 64*64 pixels and the 30 shape images of 256*256 pixels. The experimental results show that the proposed method has a superior recognition performance that appears the image characters well.

본 논문에서는 4차원의 히스토그램 기반 상관성을 이용한 효과적인 모양영상의 인식방법을 제안하였다. 여기서 히스토그램 기반 상관성은 4개 방향을 고려한 계산으로 얻어지며, 이는 영상 사이에 대응하는 차원의 위치를 비교함으로써 유사성을 좀 더 정확하게 반영하기 위함이다. 또한 상관성 척도로 정규화된 상호상관계수를 이용함으로써 모양, 위치, 크기, 회전과 같은 기하학적 변화에 강건한 인식성능을 얻기 위함이다. 제안된 방법을 8개의 $64\times64$ 픽셀의 모양영상과 30개의 $256\times256$ 픽셀의 모양영상을 대상으로 실험한 결과, 영상의 속성을 잘 반영하는 우수한 인식성능이 있음을 확인하였다.

Keywords

References

  1. 박호식, 배철수, “수화인식을 위한 얼굴과 손 추적 알고리즘,” 한국통신학회논문지, 제 31권, 제 11C호, pp. 1071-1076, 2006.
  2. 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. https://doi.org/10.1109/ICPR.2006.1050
  3. F. Mokhtarian and A. K. Mackworth, “A Theory of Multiscale, Curvature Based Shape Representation for Planar Curves,” IEEE. Trans. on Pattern Analysis and Machine Intelligence, Vol. 14. No. 8, pp. 789-805, Aug. 1992. https://doi.org/10.1109/34.149591
  4. M. K. Hu, “Visual Pattern Recognition by Moment Invariants,” IRE Trans. on Inform. Theory, Vol. 1, No. 8, pp. 179-187, Feb. 1962.
  5. S. H. Cha and S. N. Srihari, "On Measuring the Distance between Histogram," Pattern Recognition, Vol. 35, pp. 1355-1370, 2002. https://doi.org/10.1016/S0031-3203(01)00118-2
  6. F. Serratosa and A. Sanfeliu, "Signatures versus Histograms : Definitions, Distances and Algorithms," Pattern Recognition, Vol. 39, pp. 921-934, 2006. https://doi.org/10.1016/j.patcog.2005.12.005
  7. F. D. Jou, K. C. Fan, and Y. L. Chang, "Efficient Matching of Large-size Histograms," Pattern Recognition, Vol. 25, pp. 277-286, 2004. https://doi.org/10.1016/j.patrec.2003.10.005
  8. S. H. Cha, "Taxonomy of Nominal Type Histogram Distance Measures," American Conference on Applied Mathematics, Harvard, Massachusetts, USA, pp. 325-330, March 2008.
  9. 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.381-402, 2002.
  10. J. P. Lewis, "Fast Normalized Cross-Correlation," Available from http://www.idiom.com/
  11. F. Zhao, Q. Huang, and W. Gao, "Image Matching by Normalized Cross-Correlation," Available from http://jdl.ac.cn/doc/2006/
  12. 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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