The Palm Vein Graph - Feature Extraction and Matching

Arathi Arakala, Hao Hao, Stephen Davis, K. J. Horadam

2015

Abstract

We present a graphical representation for palm vein patterns for use as biometric identifiers. The palm vein image captured from an infra red camera is converted into a spatial graph. After image enhancement and binarisation, the palm vein features are extracted from the skeleton using a novel two stage spur removal technique. The location of the features and the connections between them are used to define a Palm Vein Graph. Palm vein graphs are compared using the Biometric Graph Matching (BGM) Algorithm. We propose a graph registration algorithm that improves over existing state of the art algorithms for graph registration. We introduce 10 graph topology-based measures for comparing palm vein graphs. Experiments are conducted on a public palm vein database. One of the introduced measures, an edge-based similarity, gave a definite improvement in matching accuracies over other published results on the same database, especially for samples with only a small common overlap area due to displacement. In addition, when the edge-based measure was combined with one of three other topological features, we demonstrate a further improvement in matching accuracy.

References

  1. Chen, H., Lu, G., and Wang, R. (2009). A new palm vein matching method based on icp algorithm. In Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human, pages 1207-1211, New York, USA. ACM. http://doi.acm.org/10.1145/1655925.1656145.
  2. Dubuisson, M. P. and Jain, A. (1994). A modified hausdorff distance for object matching. In Proceedings of the 12th IAPR International Conference on Pattern Recognition, pages 566-568. IEEE.
  3. Gaikwad, D. P. and Narote, S. P. (2013). Multi-modal biometric system using palm print and palm vein features. In Annual IEEE India Conference (INDICON), pages 1-5.
  4. Horadam, K. J., Davis, S. A., Arakala, A., and Jeffers, J. (2011). Fingerprints as spatial graphs: Nodes and edges. In Proc. of International Conference on Digital Image Computing Techniques and Applications (DICTA), pages 400-405, Noosa, Australia.
  5. Kabacinski, R. and Kowalski, M. (2010). Human vein pattern segmentation from low quality images - a comparison of methods. Image Processing and Communications Challenges 2, 84:105-112.
  6. Kabacinski, R. and Kowalski, M. (2011). Vein pattern database and benchmark results. Electronics Letters, 47(20):1127-1128.
  7. Kumar, A. and Prathyusha, K. V. (2009). Personal authentication using hand vein triangulation and knuckle shape. IEEE Transactions on Image Processing, 9:2127-2136.
  8. Lajevardi, S., Arakala, A., Davis, S., and Horadam, K. (2013). Retina verification system based on biometric graph matching. IEEE Transactions on Image Processing, 22(9):3625-3635.
  9. Lajevardi, S., Arakala, A., Davis, S., and Horadam, K. (2014). Hand vein authentication using biometric graph matching. IET Biometrics. doi: 10.1049/ietbmt.2013.0086.
  10. Perona, P. and Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. IEEE Transactios on Pattern Analysis and Machine Intelligence, 12:629- 639.
  11. Riesen, K. and Bunke, H. (2009). Approximate graph edit distance computation by means of bipartite graph matching. Image and Vision Computing, 27(7):950- 959.
  12. Shahin, M., Badawi, A., and Kamel, M. (2007). Biometric authentication using fast correlation of near infrared in hand vein patterns. International Journal of Biomedical Sciences, 2:141-148.
  13. Wang, L., Leedham, G., and Cho, S. Y. (2007). Infrared imaging of hand vein patterns for biometric purposes. IET Computer Vision, 1(3-4):113122.
  14. Watanabe, M., Endoh, T., Shiohara, M., and Sasaki, S. (2005). Palm vein authentication technology and its applications. In Proc. of Biometrics Consortium Conference, pages 1-2, Arlington, VA.
  15. Wenxiong, K. and Qiuxia, W. (2014). Contactless palm vein recognition using a mutual foreground-based local binary pattern. IEEE Transactions on Information Forensics and Security, 9:1974-1985.
  16. Zuiderveld, K. (1994). Contrast limited adaptive histogram equalization. Academic Press Professional, Inc., San Diego, CA, USA.
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Paper Citation


in Harvard Style

Arakala A., Hao H., Davis S. and Horadam K. (2015). The Palm Vein Graph - Feature Extraction and Matching . In Proceedings of the 1st International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-081-9, pages 295-303. DOI: 10.5220/0005239102950303


in Bibtex Style

@conference{icissp15,
author={Arathi Arakala and Hao Hao and Stephen Davis and K. J. Horadam},
title={The Palm Vein Graph - Feature Extraction and Matching},
booktitle={Proceedings of the 1st International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2015},
pages={295-303},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005239102950303},
isbn={978-989-758-081-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - The Palm Vein Graph - Feature Extraction and Matching
SN - 978-989-758-081-9
AU - Arakala A.
AU - Hao H.
AU - Davis S.
AU - Horadam K.
PY - 2015
SP - 295
EP - 303
DO - 10.5220/0005239102950303