Minutiae filtering using ridge-valley method

  1. Marco Antonio Ameller 1
  2. María Angélica González Arrieta 2
  1. 1 University Tomas Frias Potosi Bolivia
  2. 2 Universidad de Salamanca

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal

ISSN: 2255-2863

Year of publication: 2016

Volume: 5

Issue: 1

Pages: 1-10

Type: Article

DOI: 10.14201/ADCAIJ201651110 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal


Cited by

  • Web of Science Cited by: 4 (13-10-2023)
  • Dimensions Cited by: 1 (09-04-2023)
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  • Social Sciences: C


(Data updated as of 09-04-2023)
  • Total citations: 1
  • Recent citations: 0
  • Field Citation Ratio (FCR): 0.27


In order to identify subjects in a convenient and efficient way one must use some special feature that makes it possible to discriminate between persons. Some of the features are biometric in nature, such as iris texture, hand shape, the human face, and of course finger prints. These play an important role in many automatic identification systems, since every person is believed to have a unique set of fingerprints. Before a fingerprint image can be looked up in a database, it has to be classified into one of 5 types in order to reduce processing times.

Bibliographic References

  • Alonso Fernandez F.- Fierrez-Aguilar J. and Ortega-Garcia J., 2005. An Enhanced Gabor Filter-Based Segmentation Algorithm for Fingerprint Recognition Systems, In Int. Symp. on Image and Signal Processing and Analysis. http://dx.doi.org/10.1109/ispa.2005.195416
  • Arcelli C. and Baja G.S.D., 1984. A width independent fast thinning algorithm. In IEEE Transactions on Pattern Analysis Machine Intelligence.
  • Hong, L., Wan, Y. and Jain, A. K. 1998. Fingerprint image enhancement: Algorithm and performance evaluation. In IEEE Trans. Pattern Anal. Machine Intell., 20: 777–789. http://dx.doi.org/10.1109/34.709565
  • Hung D.C.D., 1993. Enhancement and feature purification of fingerprint images, Pattern Recognition.
  • Lam L. Lee S.W. and Suen C.Y., 1992. Thinning methodologies: A comprehensive survey. In IEEE Transactions on Pattern Analysis Machine Intelligence. http://dx.doi.org/10.1109/34.161346
  • Miller, B. 1994. Vital signs of identity.IEEE Spectrum, 31 (2): 22-30. http://dx.doi.org/10.1109/6.259484
  • Rao, A. R. 1990. A Taxonomy for Texture Description and Identification, New York: Springer-Verlag. http://dx.doi.org/10.1007/978-1-4613-9777-9
  • Ratha N.K. - Chen S.Y. and Jain A.K., 1995. Adaptive flow orientation-based feature extraction in fingerprint images, Pattern Recognition, 1995.
  • Woods, K.; Kegelmeyer, W.P. and Bowyer, K.W. 1997. Combination of Multiple Classifiers Using Local Accuracy Estimates. In IEEE Trans. Pattern Analysis and Machine Intelligence, 19(4): 405-410. http://dx.doi.org/10.1109/34.588027