Efficient Biometric Recognition Methodology using Guided Filtering and SIFT Feature Matching

  • Authors

    • Imran Javeed.S
    • Aanandha Saravanan
    • Rajendra Kumar
    2018-08-04
    https://doi.org/10.14419/ijet.v7i3.1.16789
  • Biometric identification, Finger vein, Gabor filter, Guided Filter, SIFT
  • A novel infrared finger vein biometric identification is proposed using Linear Gabor filter with Guidance image and SIFT feature matching. Linear Gabor filter with guidance image is used for extracting finger vein pattern without segmentation processing and also performs well with some poor quality images due to low contrast, illuminance imbalance or noise etc. Firstly, we utilized Guided Linear Gabor filter for ridge detection as simple Linear Gabor filter and also enhance the image by performing edge preserving smoothing operation. Secondly we utilized SIFT feature matching for verification. A SIFT (Scale Invariant Feature Transform) can extract features to posses rotation invariance and shift invariance for providing better matching rate. The simulation analysis shows our proposed system is an effective feature for finger vein biometric identification.

     

  • References

    1. [1] Kono, M., Ueki, H., Umemura, S., “Near-infrared finger vein patterns for personal identification,†Appl.Opt.41(35),2002, pp. 7429-7436.

      [2] N. Miura, A. Nagasaka, and T. Miyatake, “Feature Extraction of finger- vein patterns based on repeated line tracking and its Applicationto Personal Identification,†Machine Vision and Applications, Vol. 15,No. 4, 2004, pp. 194-203.

      [3] Yanagawa, T., Aoki, S., Ohyama, T., “Human finger vein images are diverse and its patterns are useful for personal identification.MHF Preprint Series,†MHF 2007-12, Kyushu University 21st Century COE Program, Development of Dynamic Mathematics with High Functionality, 2007.

      [4] D.Mulyono, H.Jinn, “A Study of Finger Vein Biometric for Personal Identification,†International Symposium on Biometrics and Security Technologies, ISBAST'08, 2008, pp. 1-8.

      [5] A. Materka, and M. Strzelecki, “Texture Analysis Methods – A Review,†Technical Report. Institute of Electronics, Technical University of Lodz, Brussels. 1998.

      [6] Rosniza Roslan, Nursuiati Jamil, “Texture Feature Extraction using 2-D Linear Gabor filters,†ISCAIE, 2012, pp. 173-178.

      [7] A. K. Jain, N. K. Ratha, and S. Lakshmanan, “Object Detection using Linear Gabor filters.†Pattern Recognition, Vol. 30(2), 295–309, 1997.

      [8] J. Y. Tou, Y. H. Tay, and P. Y. Lau, “Linear Gabor filters and Grey-level Co- occurrence Matrices in Texture Classification,†MMU International Symposium on Information and Communications Technologies, 1-5 2007.

      [9] N. Seo, “Texture Segmentation using Linear Gabor filters,†University of Maryland, Technical Report, 2006.

      [10] K. G. Derpanis, “Linear Gabor filters,†York University, Technical Report. 2007.

      [11] D. Zhang, A. Wong, M. Indrawan, and G. Lu, “Content-based Image Retrieval Using Gabor Texture Features,†IEEE Pacific-Rim on Multimedia (PCM00), 1139–1142, 2000.

      [12] Shan Juan Xie, JuCheng Yang, Sook Yoon, Lu Yu and Dong Sun Park, “Guided Linear Gabor filter for Finger Vein Pattern Extraction,†International Conference on Signal Image Technology and Internet Based System. 2012, 19, pp. 118-123.

      [13] Jialiang Peng, Ning Wang, Ahmed A.Abd El-Latif, Qiong Li, Xiamu Niu“ Finger-vein verification using Linear Gabor filter and SIFT Feature Matching,†, International Conference on Intelligent Information Hiding and Multimedia Signal Processing.2012, pp. 45-48.

      [14] WANG Yun-Xin, WANG Da-Yong, LIU Tie-Gen, et al, “Local SIFT analysis for hand vein pattern verificationâ€, Proc. SPIE,

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  • How to Cite

    Javeed.S, I., Saravanan, A., & Kumar, R. (2018). Efficient Biometric Recognition Methodology using Guided Filtering and SIFT Feature Matching. International Journal of Engineering & Technology, 7(3.1), 23-26. https://doi.org/10.14419/ijet.v7i3.1.16789