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Finger Print Recognition by Background Subtraction and Image


Affiliations
1 Department of Electronics and Communication Engineering, Kalyani Government Engineering College, Kalyani- 741235, Dist. Nadia, West Bengal, India
 

The fingerprint identification based on Image enhancement technique is essential for crime scene investigation, authentication of a person. The most challenging fields of computer aided design is to identify a person by his or her fingerprint. In this paper, the quality of each image in the input sequence is assessed and a clear fingerprint is selected from such a sequence for subsequent recognition. After preprocessing, an effective fingerprint image is extracted from the original image. Thereafter, features are extracted from image and those features are analyzed to match with a reference image feature. For this, an algorithm is developed and coded in MATLAB (R2015a).

Keywords

Finger Print, Image Analysis, Gamma Correction, Image Enhancement.
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  • Hong, L., Jain, A. K.,Pankanti, S. and Bolle, R., Fingerprint Enhancement, Proceedings ofIEEE Workshop on Applications of Computer Vision, Sarasota, FL, pp. 202-207, 1996.
  • Hong, L., Wan, Y. and Jain, A.K., Fingerprint Image Enhancement: Algorithms and Performance Evaluation, IEEE Transactions on PAMI ,Vol. 20, No. 8, pp.777-789, 1998.
  • Maio, D. and Maltoni, D., Direct gray-scale minutiae detection in fingerprints, IEEE Trans.Pattern Anal. and Machine Intell,Vol. 19(1), pp. 27-40, 1997.
  • Jain, A.K., Hong, L., and Bolle, R, On-Line Fingerprint Verification, IEEE Trans. On Pattern Anal and Machine Intell, Vol. 19(4), pp. 302-314, 1997.
  • Coetzee, L. and Botha, E. C., Fingerprint Recognition in Low Quality Images, Pattern Recognition, Vol. 26, No. 10, pp. 1441-1460, 1993.
  • Lange ,L. and Leopold, G., Digital identification: It’s now at our fingertips, EEtimes at http://techweb.cmp.com/eet/ 823/, March 24, Vol. 946, 1997.
  • Ratha, N.,Chen, S. and . Jain, A.K., Adaptive Flow Orientation Based Feature Extraction in Fingerprint Images, Pattern Recognition, Vol. 28, pp. 1657-1672, 1995.
  • Zsolt, A. M., Vajna, K., and Leone, A., Fingerprint minutiae extraction from skeletonized binary images, Pattern Recognition, Vol.32, No.4, pp877-889, 1999.
  • Hong, L., Automatic Personal Identification Using Fingerprints, Ph.D. Thesis, 1998.
  • Germain, R., Califano, A., and Colville, S., Fingerprint matching using transformation parameter clustering, IEEE Computational Science and Engineering, Vol. 4, No. 4, pp. 42–49, 1997.
  • Sudiro, S. A., Paindavoine, M., and Kusuma, T. M., Simple Fingerprint Minutiae Extraction Algorithm Using Crossing Number On Valley Structure, Automatic Identification AdvancedTechnologies, IEEE Workshop on, Alghero, Italy, DOI: 10.1109/AUTOID.2007.380590, 2007.
  • Parra, P., Fingerprint minutiae extraction and matching for identification procedure, University of California, San Diego La Jolla, CA (2004): 92093-0443, 2004.
  • Zaeri, N., Minutiae-based Fingerprint Extraction and Recognition, Biometrics, Jucheng Yang (Ed.), ISBN: 978-953-307-618-8, InTech, http://www.intechopen.com/ bo oks/biomet r ics /minut iae-base dfingerprintextraction-and-recognition, 2011.
  • Shin, J. H., Hwang, H. Y., and Chien, S. I., Minutiae Extraction from Fingerprint Images Using Run-Length Code, Proceedings of ISMIS 2003: Foundations of Intelligent Systems, pp. 577-584, 2003.
  • Fronthaler, H., Kollreider, K., and Bigun, J., Local features for enhancement and minutiae extraction in fingerprints, IEEE Trans Image Process. Vol. 17(3), pp. 354-63, DOI: 10.1109/TIP.2007.916155, 2008.
  • Singh, B., and Singh, I., Fingerprint Minutiae Extraction and Compression Using LZW Algorithm, International Journal for Scientific Research& Development| Vol. 2, Issue 07, ISSN (online): 2321-0613, 2014.
  • Pawar, S., Ghodke, A., Gaikwad, B. P., and Wakhude, G. P., A Survey of Minutiae Extraction from Various Fingerprint Images, IJARCSSE, Vol. 6(6), pp. 169-173, 2016.
  • Singh, I. and Sharma, R., A Survey on Fingerprint Minutiae Extraction, International Journal of Advance Research, Ideas and Innovations in Technology, Vol. 3(3), pp. 264-267, 2017.

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  • Finger Print Recognition by Background Subtraction and Image

Abstract Views: 525  |  PDF Views: 127

Authors

Bandana Barman
Department of Electronics and Communication Engineering, Kalyani Government Engineering College, Kalyani- 741235, Dist. Nadia, West Bengal, India
Supratim Roy
Department of Electronics and Communication Engineering, Kalyani Government Engineering College, Kalyani- 741235, Dist. Nadia, West Bengal, India

Abstract


The fingerprint identification based on Image enhancement technique is essential for crime scene investigation, authentication of a person. The most challenging fields of computer aided design is to identify a person by his or her fingerprint. In this paper, the quality of each image in the input sequence is assessed and a clear fingerprint is selected from such a sequence for subsequent recognition. After preprocessing, an effective fingerprint image is extracted from the original image. Thereafter, features are extracted from image and those features are analyzed to match with a reference image feature. For this, an algorithm is developed and coded in MATLAB (R2015a).

Keywords


Finger Print, Image Analysis, Gamma Correction, Image Enhancement.

References





DOI: https://doi.org/10.21843/reas%2F2016%2F54-60%2F158776