Abstract
This paper presents the use of a genetic algorithm and genetic programming for the enhancement of an automatic fingerprint identification system (AFIS). The recognition engine within the original system functions by transforming the input fingerprint into a feature vector or fingercode using a Gabor filter bank and attempting to create the best match between the input fingercode and the database fingercodes. A decision to either accept or reject the input fingerprint is then carried out based upon whether the norm of the difference between the input fingercode and the best-matching database fingercode is within the threshold or not. The efficacy of the system is in general determined from the combined true acceptance and true rejection rates. In this investigation, a genetic algorithm is applied during the pruning of the fingercode while the search by genetic programming is executed for the purpose of creating a mathematical function that can be used as an alternative to the norm operator. The results indicate that with the use of both genetic algorithm and genetic programming the system performance has improved significantly.
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References
Galton, F.: Finger Prints. Macmillan, London (1892)
Henry, E.R.: Classification and Uses of Finger Prints. HM Stationary Office, London (1905)
Moayer, B., Fu, K.S.: A tree system approach for fingerprint pattern recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(3), 376–387 (1986)
Blue, J.L., Candela, G.T., Grother, P.J., Chellappa, R., Wilson, C.L.: Evaluation of pattern classifiers for fingerprint and OCR applications. Pattern Recognition 27(4), 485–501 (1994)
Rao, T.C.M.: Feature extraction for fingerprint classification. Pattern Recognition 8(3), 181–192 (1976)
Hrechak, A.K., McHugh, J.A.: Automated fingerprint recognition using structural matching. Pattern Recognition 23(8), 893–904 (1990)
Karu, K., Jain, A.K.: Fingerprint classification. Pattern Recognition 29(3), 389–404 (1996)
Hong, L., Jain, A.K.: Classification of fingerprint images. In: Proceedings of the 11th Scandinavian Conference on Image Analysis, Kangerlussuaq, Greenland (1999)
Cho, B.-H., Kim, J.-S., Bae, J.-H., Bae, I.-G., Yoo, K.-Y.: Core-based fingerprint image classification. In: Proceedings of the 15th International Conference on Pattern Recognition, Barcelona, Spain, pp. 859–862 (2000)
Mitra, S., Pal, S.K., Kundu, M.K.: Fingerprint classification using a fuzzy multilayer perceptron. Neural Computing and Applications 2(4), 227–233 (1994)
Halici, U., Ongun, G.: Fingerprint classification through self-organizing feature maps modified to treat uncertainties. Proceedings of the IEEE 84(10), 1497–1512 (1996)
Jain, A.K., Prabhakar, S., Hong, L.: A multichannel approach to fingerprint classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(4), 348–359 (1999)
Coetzee, L., Botha, E.C.: Fingerprint recognition in low quality images. Pattern Recognition 26(10), 1441–1460 (1993)
Farina, A., Kovács-Vajna, Z.M., Leone, A.: Fingerprint minutiae extraction from skeletonized binary images. Pattern Recognition 32(5), 877–889 (1999)
Fan, K.C., Liu, C.W., Wang, Y.K.: A randomized approach with geometric constraints to fingerprint verification. Pattern Recognition 33(11), 1793–1803 (2000)
Tan, X., Bhanu, B.: Robust fingerprint identification. In: Proceedings of the, International Conference on Image Processing, Rochester, NY, pp. I-277–I-280 (2002)
Tan, X., Bhanu, B.: Fingerprint matching by genetic algorithms. In: Late Breaking Papers at the 2002 Genetic and Evolutionary Computation Conference, New York, NY, pp. 435–442 (2002)
Tan, X., Bhanu, B.: Fingerprint verification using genetic algorithms. In: Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision, Orlando, FL, pp. 79–83 (2002)
Tan, X., Bhanu, B.: Fingerprint matching by genetic algorithms. Pattern Recognition 39(3), 465–477 (2006)
Jain, A.K., Prabhakar, S., Hong, L., Pankanti, S.: Filterbank-based fingerprint matching. IEEE Transactions on Image Processing 9(5), 846–859 (2000)
Goldberg, D.E.: Genetic Algorithms: In Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Koza, J.R.: Genetic Programming: On the Programming by Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
Daugman, J.G.: High confidence visual recognition of persons by a test of statistical independence. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(11), 1148–1161 (1993)
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Wetcharaporn, W., Chaiyaratana, N., Huvanandana, S. (2006). Enhancement of an Automatic Fingerprint Identification System Using a Genetic Algorithm and Genetic Programming. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_33
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DOI: https://doi.org/10.1007/11732242_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33237-4
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