Fingerprint registration using genetic algorithms

In automated fingerprint identification systems, an efficient and accurate alignment algorithm in the preprocessing stage plays a crucial role in the performance of the whole system. We explore the use of genetic algorithms for optimizing the alignment of a pair of fingerprint images. To test its performance, we compare the implemented genetic algorithm with two other algorithms, namely, 2D and 3D algorithms. Based upon our experiment on 250 pairs of fingerprint images, we find that: genetic algorithms run ten times faster than a 3D algorithm with similar alignment accuracy; and genetic algorithms are 13% more accurate than a 2D algorithm, with the same running time. The conclusion drawn from this study is that a genetic algorithm approach is an efficient and effective approach for fingerprint image registration.

[1]  John Daniel. Bagley,et al.  The behavior of adaptive systems which employ genetic and correlation algorithms : technical report , 1967 .

[2]  Hayong Harry Zhou,et al.  Conceptual learning and classifier systems with long-term memory , 1991, CSC '91.

[3]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[4]  Hayong Zhou.  Classifier Systems with Long Term Memory , 1985, ICGA.

[5]  R. Brady.  Optimization strategies gleaned from biological evolution , 1985, Nature.

[6]  Richard S. Rosenberg,et al.  Stimulation of genetic populations with biochemical properties: I. The model , 1970 .

[7]  D. J. Cavicchio,et al.  Reproductive adaptive plans , 1972, ACM Annual Conference.

[8]  Richard S. Rosenberg,et al.  Simulation of genetic populations with biochemical properties. II. Selection of crossover probabilities. , 1970 .

[9]  Riva Wenig Bickel,et al.  Tree Structured Rules in Genetic Algorithms , 1987, ICGA.

[10]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Hany H. Ammar,et al.  Parallel Processing and Fingerprint Image Comparison , 1998 .

[13]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[14]  Michael P. Fourman,et al.  Compaction of Symbolic Layout Using Genetic Algorithms , 1985, ICGA.

[15]  Dirk Van Gucht,et al.  Incorporating Heuristic Information into Genetic Search , 1987, International Conference on Genetic Algorithms.