A New Approach for Fingerprint Classification based on Minutiae Distribution
The paper describes a new approach for fingerprint
classification, based on the distribution of local features (minute
details or minutiae) of the fingerprints. The main advantage is that
fingerprint classification provides an indexing scheme to facilitate
efficient matching in a large fingerprint database. A set of rules based
on heuristic approach has been proposed. The area around the core
point is treated as the area of interest for extracting the minutiae
features as there are substantial variations around the core point as
compared to the areas away from the core point. The core point in a
fingerprint has been located at a point where there is maximum
curvature. The experimental results report an overall average
accuracy of 86.57 % in fingerprint classification.
[1] Galton F., Finger prints, McMillan, London, 1892.
[2] Henry E., Classification and uses of finger prints, Routledge, London,
1900.
[3] Kowagoe M. and Tojo A., "Fingerprints Pattern Classification," Pattern
Recognition, vol.17, pp. 295-303, 1984.
[4] Karu K., Jain A. K., "Fingerprint Classification," Pattern Recognition,
vol. 29, no.3, pp. 389-404, 1996.
[5] Hong L., Jain A. K., "Classification of Fingerprint Images," in
Proc.Scandinvan Conf. on Image Analysis (11th), 1999.
[6] Cho B. H., Kim J. S., Bae J. H., Bae I. G., and Yoo K. Y., " Core-Based
Fingerprint Image Classification," in Proc. Int. Conf. on Pattern
Recognition (15th), vol. 2, pp. 863-866, 2000.
[7] Jain A. K., and Minut S., "Hierarchical Kernel Fitting for Fingerprint
Classification and Alignment," in Proc. Int. Conf. on Pattern
Recognition (16th), vol. 2, pp. 469-473, 2002.
[8] Maio D., Maltoni D., "A Structural Approach to Fingerprint
Classification," in Proc. Int. Conf. On Pattern Recognition (13th), 1996.
[9] Chappelli R., Lumini A., Maio D., and Maltoni D., "Fingerprint
Classification by Directional Image Partitioning," IEEE Transactions on
Pattern Analysis and machine Intelligence, vol. 21, no. 5 pp. 402-421,
1999.
[10] Senior A., "A Hidden Markov Model Fingerprint Classifier," in Proc.
Asilomar Conf. on Signals Systems and Computers (31st), pp. 306-
310,1997.
[11] H.C.Lee and R E Gaensslen. Advances in Fingerprint Technology.
Elsevier, New York 1991.
[12] L. Hong and A. K. Jain, "Classification of Fingerprint Images," 11th
Scandinavian Conference on Image Analysis, June 7-11, Kangerlussuaq,
Greenland, 1999.
[13] A Ravishankar Rao, "A Taxonomy for Texture Description and
Identification", Springer Verlag, New York 1990.
[14] Jayadevan.R,Jayant V Kulkarni,Suresh N Mali,Hemant K Abhyankar "A
new ridge Orientation Based Method of Computation for Feature
Extraction from Fingerprint Images"13th World Enformatika Conference
on Pattern Analysis May 26-28,Budapest,Hungary 2006.
[15] B.M. Mehtre, "Fingerprint image analysis for automatic identification",
Machine Vision and Applications Vol 6, pp.124-139, 1993.
[16] Amengual, J. C., Juan, A., Prez, J. C., Prat, F., Sez, S., and Vilar, J. M.
"Real-time minutiae extraction in fingerprint images". In Proc. of the 6th
Int. Conf. on Image Processing and its Applications, pp. 871-875, July
1997.
[17] Q. Xiao and H. Raafat. "Fingerprint image post processing A
combined statistical and structural approach", Pattern Recognition Vol.
24, No.10: pp. 985-992, 1991.
[1] Galton F., Finger prints, McMillan, London, 1892.
[2] Henry E., Classification and uses of finger prints, Routledge, London,
1900.
[3] Kowagoe M. and Tojo A., "Fingerprints Pattern Classification," Pattern
Recognition, vol.17, pp. 295-303, 1984.
[4] Karu K., Jain A. K., "Fingerprint Classification," Pattern Recognition,
vol. 29, no.3, pp. 389-404, 1996.
[5] Hong L., Jain A. K., "Classification of Fingerprint Images," in
Proc.Scandinvan Conf. on Image Analysis (11th), 1999.
[6] Cho B. H., Kim J. S., Bae J. H., Bae I. G., and Yoo K. Y., " Core-Based
Fingerprint Image Classification," in Proc. Int. Conf. on Pattern
Recognition (15th), vol. 2, pp. 863-866, 2000.
[7] Jain A. K., and Minut S., "Hierarchical Kernel Fitting for Fingerprint
Classification and Alignment," in Proc. Int. Conf. on Pattern
Recognition (16th), vol. 2, pp. 469-473, 2002.
[8] Maio D., Maltoni D., "A Structural Approach to Fingerprint
Classification," in Proc. Int. Conf. On Pattern Recognition (13th), 1996.
[9] Chappelli R., Lumini A., Maio D., and Maltoni D., "Fingerprint
Classification by Directional Image Partitioning," IEEE Transactions on
Pattern Analysis and machine Intelligence, vol. 21, no. 5 pp. 402-421,
1999.
[10] Senior A., "A Hidden Markov Model Fingerprint Classifier," in Proc.
Asilomar Conf. on Signals Systems and Computers (31st), pp. 306-
310,1997.
[11] H.C.Lee and R E Gaensslen. Advances in Fingerprint Technology.
Elsevier, New York 1991.
[12] L. Hong and A. K. Jain, "Classification of Fingerprint Images," 11th
Scandinavian Conference on Image Analysis, June 7-11, Kangerlussuaq,
Greenland, 1999.
[13] A Ravishankar Rao, "A Taxonomy for Texture Description and
Identification", Springer Verlag, New York 1990.
[14] Jayadevan.R,Jayant V Kulkarni,Suresh N Mali,Hemant K Abhyankar "A
new ridge Orientation Based Method of Computation for Feature
Extraction from Fingerprint Images"13th World Enformatika Conference
on Pattern Analysis May 26-28,Budapest,Hungary 2006.
[15] B.M. Mehtre, "Fingerprint image analysis for automatic identification",
Machine Vision and Applications Vol 6, pp.124-139, 1993.
[16] Amengual, J. C., Juan, A., Prez, J. C., Prat, F., Sez, S., and Vilar, J. M.
"Real-time minutiae extraction in fingerprint images". In Proc. of the 6th
Int. Conf. on Image Processing and its Applications, pp. 871-875, July
1997.
[17] Q. Xiao and H. Raafat. "Fingerprint image post processing A
combined statistical and structural approach", Pattern Recognition Vol.
24, No.10: pp. 985-992, 1991.
@article{"International Journal of Information, Control and Computer Sciences:56640", author = "Jayant V Kulkarni and Jayadevan R and Suresh N Mali and Hemant K Abhyankar and Raghunath S Holambe", title = "A New Approach for Fingerprint Classification based on Minutiae Distribution", abstract = "The paper describes a new approach for fingerprint
classification, based on the distribution of local features (minute
details or minutiae) of the fingerprints. The main advantage is that
fingerprint classification provides an indexing scheme to facilitate
efficient matching in a large fingerprint database. A set of rules based
on heuristic approach has been proposed. The area around the core
point is treated as the area of interest for extracting the minutiae
features as there are substantial variations around the core point as
compared to the areas away from the core point. The core point in a
fingerprint has been located at a point where there is maximum
curvature. The experimental results report an overall average
accuracy of 86.57 % in fingerprint classification.", keywords = "Minutiae distribution, Minutiae, Classification,
Orientation, Heuristic.", volume = "2", number = "3", pages = "793-6", }