Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Palmprint Verification Using the Histogram of Local Binary Patterns

국부 이진패턴 히스토그램을 이용한 장문인식

  • 김민기 (경상대학교 컴퓨터교육과, 컴퓨터정보통신연구소)
  • Received : 2010.07.31
  • Accepted : 2010.08.27
  • Published : 2010.10.31
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Abstract

This paper proposes an efficient method for verifying palmprint which is captured at the natural interface without any physical restriction. The location and orientation of the region of interest (ROI) in palm images are variously appeared due to the translation and rotation of hand. Therefore, it is necessary to extract the ROI stably for palmprint recognition. This paper presents a method that can extract the ROI, which is based on the reference points that are located at the center of the crotch segments between index finger and middle finger and between ring finger and little finger. It also proposes a palmprint recognition method using the histogram of local binary patterns (LBP). Experiments for evaluating the performance of the proposed method were performed on 1,597 palmprint images acquired from 100 different persons. The experimental results showed that ROI was correctly extracted at the rate of 99.5% and the equal error rate (EER) and the decidability index d' indicating the performance of palmprint verification were 0.136 and 3.539, respectively. These results demonstrate that the proposed method is robust to the variations of the translation and rotation of hand.

본 논문은 물리적 제약이 없는 자연스러운 인터페이스에서 획득한 장문영상을 효과적으로 인식하는 방법을 제안한다. 손의 위치 이동이나 회전으로 인하여 손바닥 영상에서 관심영역의 위치나 방향이 다양하게 나타나므로, 장문인식을 위해서는 안정적인 관심영역 추출이 필요하다. 본 논문은 검지와 중지, 소지와 약지 사이의 손 가랑이 구간의 중심점을 기준으로 관심영역을 추출하는 방법을 제시하고, 국부 이진패턴 히스토그램을 이용한 장문인식 방법을 제안한다. 제안된 방법의 성능을 측정하기 위하여 100인으로부터 획득한 총 1,597개의 장문영상을 대상으로 실험을 수행하였다. 실험 결과 ROI 추출 성공률이 99.5%였고, 장문인식 성능을 보여주는 동일오류율과 결정계수 d'를 측정한 결과 각각 0.136, 3.539를 보였다. 이러한 결과는 제안된 방법이 손의 위치나 회전 변형에 강인함을 나타낸다.

Keywords

References

  1. 신광규, 이강현, "Hu 불변 모멘트를 이용한 장문인식 알고리즘," 전자공학회논문지, 제 42권, 제 2호, 31-38쪽, 2005년 3월.
  2. G. Lu, D. Zhang, K. Wang, "Palmprint Recognition Using Eignepalms Features," Pattern Recognition Letters, Vol. 24, pp.1463-1467, 2003. https://doi.org/10.1016/S0167-8655(02)00386-0
  3. X. Wu, D. Zhang, K. Wang, "Fisherpalms Based Palmprint Recognition," Pattern Recognition Letters, Vol. 24, pp. 2829-2838, 2003. https://doi.org/10.1016/S0167-8655(03)00141-7
  4. A.W.K. Kong, D. Zhang, "Competitive Coding Scheme for Palmprint Verification," Proc. of the 17th ICPR, Vol. 1, pp. 520-523, 2004.
  5. X. Wu, K. Wang, D. Zhang, "Palmprint Authentification Based on Orientation Code Matching," AVBPA 2005, LNCS 3546, pp. 555-562, 2005.
  6. W. Jia, D.-S. Huang, D. Zhang, "Palmprint Verification Based on Robust Line Orientation Code," Pattern Recognition, Vol. 41, pp. 1504-1513, 2008. https://doi.org/10.1016/j.patcog.2007.10.011
  7. D. Zhang, W.-K. Kong, J. You, M. Wong, "Online Palmprint Identification," IEEE Trans. on PAMI, Vol. 25, No. 9, pp. 1041-1050, 2003. https://doi.org/10.1109/TPAMI.2003.1227981
  8. T. Ojala, M. Pietikainen, D. Harwood, "A Comparative Study of Texture Measures with Classification Based on Feature Distributions," Pattern Recognition, Vol. 29, No. 1, pp. 51-59, 1996. https://doi.org/10.1016/0031-3203(95)00067-4
  9. T. Ojala, M. Pietikanen, T. Maenpaa, "Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns," IEEE Trans. on PAMI, Vol. 24, No. 7, pp. 971-987, 2002. https://doi.org/10.1109/TPAMI.2002.1017623
  10. T. Ahonen, A. Hadid, M. Pietikainen, "Face Recognition with Local Bianry Patterns," ECCV 2004, LNCS 3021, pp. 469-481, 2004.
  11. V. Takala, T.Ahonen, M. Pietikainen, "Block- Based Methods for Image Retrieval Using Local Binary Patterns," SCIA 2005, LNCS 3540, pp. 882-891, 2005.
  12. A. Kumar, D.C. Wong, H.C. Shen, A.K. Jain, "Personal Verification using Palmprint and Hand Geometry Biometric," Proc. of the 4th International Conference on Audio- and Videobased Biometric Person Authentification, pp. 668-678, 2003.
  13. P. Shang, T. Li, "Multifractal characteristics of palmprint and its extracted algorithm," Applied Mathematical Modeling, Vol. 33, pp. 4378- 4387, 2009. https://doi.org/10.1016/j.apm.2009.03.009
  14. 김민기, "장문인식을 위한 적응적 관심영역 추출 방법," 한국콘텐츠학회 춘계종합학술대회 논문집, 제 8권, 제1호, 336-338쪽, 2010년 5월.
  15. N. Otsu, "A Threshold Selection Method from Gray Level Histograms," IEEE Trans. on SMC, Vol. 9, pp. 62-66, 1979.
  16. CASIA-PalmprintV1, available at http://www.cbsr.ia. ac.cn/PalmDatabase.htm.
  17. J. Daugman, "The importance of beging random: statistical principals of iris recognition." Vol. 36, pp. 279-291, 2003. https://doi.org/10.1016/S0031-3203(02)00030-4