Hand Recognition using Texture Histograms - A Proposed Technique for Image Acquisition and Recognition of the Human Palm

Luiz Antônio Pereira Neves, Dionei José Müller, Fellipe Alexandre, Pedro Machado Guillen Trevisani, Pedro Santos Brandi, Rafael Junqueira

2014

Abstract

This paper presents a technique for biometric identification based on image acquisition of the palm of the human hand. A computer system called Palm Print Authentication System (PPAS) was implemented using the technique exposed, it identifies human hand palm by processing image data through texture identification and geometrical data by employing the Local Binary Pattern (LBP) method. The methodology proposed has four steps: image acquisition; image pre-processing (normalization), and segmentation for biometric extraction and hand recognition. The technique has been tested utilizing 50 different images and the tests have proven promising results, showing that the approach is not only robust but also quite efficient.

References

  1. Bakina, I. (2011). Palm shape comparison for person recognition. In VISAPP'11 Proceedings of the International Conference on Computer Vision Theory and Applications 2011, pages 5- 11.
  2. Facon, J. (1996). Morfologia matemtica: teoria e exemplos. Editor Jacques Facon.
  3. Gonzalez, R. C. and Woods, R. E. (2007). Digital Image Processing. Prentice Hall.
  4. Jemma, S. B. and Hammami, M. (2011). Palmprint recognition based on regions selection. In VISAPP'11 Proceedings of the International Conference on Computer Vision Theory and Applications 2011, pages 320-325.
  5. Khan, M. and Khan, N. (2009). A new method to extract dorsal hand vein pattern using quadratic inference function. International Journal of Computer Science and Information Security, 6(3):26-30.
  6. Kumar, A. and Shen, H. (2003). Recognition of palmprints using eigenpalm. In Proceedings of the International Conference on Computer Vision Pattern Recognition and Image Processing 2003.
  7. Li, F., Leung, M., and Chiang, C. (2009). Making palm print matching mobile. International Journal of Computer Science and Information Security, 6(2):1-9.
  8. Ojala, T., Pietikainen, M., and Harwoork, D. (1996). A comparative Study of texture measures with classification based on feature distribution. Pattern Recognition (PR), 29(1):51-59.
  9. Ojala, T., Pietikainen, M., and Maenpaa, T. (2002). Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transaction on Pattern Analysis and Machine Intelligence (PA MI), 27(7):971-987.
  10. OPENCV (2011). Open Computer Vision Library http://sourceforge.net/projects/opencvlibrary/.
  11. Otsu, N. (1979). A threshold selection method from graylevel histograms. IEEE Transactions on Systems, Man and Cybernetics, 9(1):62-69.
  12. P.K., M. and Swamy, M. S. (2010). An efficient process of human recognition fusing palmprint and speech features. International Journal of Computer Science and Information Security, 6(11):1-6.
  13. Ribarc, S. (2005). A biometric identification system based on eigenpalm and eigenfinger features. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(11):1698-1709.
  14. Wu, X., Zhang, D., Wang, K., and Huang, B. (2004). Palmprint classification using principal lines. Pattern Recognition,, pages 1987-1998.
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Paper Citation


in Harvard Style

Pereira Neves L., Müller D., Alexandre F., Trevisani P., Brandi P. and Junqueira R. (2014). Hand Recognition using Texture Histograms - A Proposed Technique for Image Acquisition and Recognition of the Human Palm . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 180-185. DOI: 10.5220/0004692601800185


in Bibtex Style

@conference{visapp14,
author={Luiz Antônio Pereira Neves and Dionei José Müller and Fellipe Alexandre and Pedro Machado Guillen Trevisani and Pedro Santos Brandi and Rafael Junqueira},
title={Hand Recognition using Texture Histograms - A Proposed Technique for Image Acquisition and Recognition of the Human Palm},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={180-185},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004692601800185},
isbn={978-989-758-009-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Hand Recognition using Texture Histograms - A Proposed Technique for Image Acquisition and Recognition of the Human Palm
SN - 978-989-758-009-3
AU - Pereira Neves L.
AU - Müller D.
AU - Alexandre F.
AU - Trevisani P.
AU - Brandi P.
AU - Junqueira R.
PY - 2014
SP - 180
EP - 185
DO - 10.5220/0004692601800185