Browse > Article
http://dx.doi.org/10.9708/jksci.2010.15.10.027

Palmprint Verification Using the Histogram of Local Binary Patterns  

Kim, Min-Ki (경상대학교 컴퓨터교육과, 컴퓨터정보통신연구소)
Publication Information
Journal of the Korea Society of Computer and Information / v.15, no.10, 2010 , pp. 27-34 More about this Journal
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.
Keywords
Palmprint Verification; Region of Interest; Local Binary Patterns;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 W. Jia, D.-S. Huang, D. Zhang, "Palmprint Verification Based on Robust Line Orientation Code," Pattern Recognition, Vol. 41, pp. 1504-1513, 2008.   DOI   ScienceOn
2 D. Zhang, W.-K. Kong, J. You, M. Wong, "Online Palmprint Identification," IEEE Trans. on PAMI, Vol. 25, No. 9, pp. 1041-1050, 2003.   DOI   ScienceOn
3 N. Otsu, "A Threshold Selection Method from Gray Level Histograms," IEEE Trans. on SMC, Vol. 9, pp. 62-66, 1979.
4 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.   DOI   ScienceOn
5 P. Shang, T. Li, "Multifractal characteristics of palmprint and its extracted algorithm," Applied Mathematical Modeling, Vol. 33, pp. 4378- 4387, 2009.   DOI   ScienceOn
6 김민기, "장문인식을 위한 적응적 관심영역 추출 방법," 한국콘텐츠학회 춘계종합학술대회 논문집, 제 8권, 제1호, 336-338쪽, 2010년 5월.
7 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.   DOI   ScienceOn
8 T. Ahonen, A. Hadid, M. Pietikainen, "Face Recognition with Local Bianry Patterns," ECCV 2004, LNCS 3021, pp. 469-481, 2004.
9 V. Takala, T.Ahonen, M. Pietikainen, "Block- Based Methods for Image Retrieval Using Local Binary Patterns," SCIA 2005, LNCS 3540, pp. 882-891, 2005.
10 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.
11 CASIA-PalmprintV1, available at http://www.cbsr.ia. ac.cn/PalmDatabase.htm.
12 X. Wu, D. Zhang, K. Wang, "Fisherpalms Based Palmprint Recognition," Pattern Recognition Letters, Vol. 24, pp. 2829-2838, 2003.   DOI   ScienceOn
13 A.W.K. Kong, D. Zhang, "Competitive Coding Scheme for Palmprint Verification," Proc. of the 17th ICPR, Vol. 1, pp. 520-523, 2004.
14 X. Wu, K. Wang, D. Zhang, "Palmprint Authentification Based on Orientation Code Matching," AVBPA 2005, LNCS 3546, pp. 555-562, 2005.
15 신광규, 이강현, "Hu 불변 모멘트를 이용한 장문인식 알고리즘," 전자공학회논문지, 제 42권, 제 2호, 31-38쪽, 2005년 3월.   과학기술학회마을
16 G. Lu, D. Zhang, K. Wang, "Palmprint Recognition Using Eignepalms Features," Pattern Recognition Letters, Vol. 24, pp.1463-1467, 2003.   DOI   ScienceOn
17 J. Daugman, "The importance of beging random: statistical principals of iris recognition." Vol. 36, pp. 279-291, 2003.   DOI   ScienceOn