Biometric Hashing Based on Genetic Selection and Its Application to On-Line Signatures

The authors present a general biometric hash generation scheme based on vector quantization of multiple feature subsets selected with genetic optimization. The quantization of subsets overcomes the dimensionality problem of other hash generation algorithms, while the feature selection step using an integer-coding genetic algorithm enables to exploit all the discriminative information found in large feature sets. They provide experimental results of the proposed hashing for verification of on-line signatures. Development and evaluation experiments are reported on the MCYT signature database, comprising 16,500 signatures from 330 subjects.