The Optimize And Investigation Of Fingerprint Identification Based On Intergenerational Differential Genetic Algorithms

With the importance of the identity identification raising continuously, the application of fingerprint identification is more and more wide. A variety of identifications,such as, the government welfare issues, examining, all of those can be relate to fingerprint identification.Fingerprint identification is a mature biology identification. It is based on opposite stability and unique of human fingerprint. And automated fingerprint identification system makes use of a calculator to carry on. Comparing the fingerprint with the one which been kept in the fingerprint database, can confirm one's actual identity.Image compression is a very important step during the process of the fingerprint identification. However just involving some limited informations of fingerprint when the calculator handles a fingerprint, it can not always provide the absolutely accurate result. The current automated fingerprint identification system has a great many disadvantages, such as complicated processing, a lot of data to deal with, the slow matching speed, single arithmetic, inaccurate identity and so on.Fractal encoding is an especial image compression method,and the compressed rate is related to the contents. The idea of the fractal encoding is based on self-affine characteristics of the image. Using the partitioned iterated Function system, can we restore the image with a small aumount of data.Genetic algorithms, as a computational model simulating the biological evolution process of the genetic selection theory of Dar-win, is a whole new global optimization algorithm and is widely used in many fields with its remarkable characteristic of simplicity, commonability, stability, suitability for parallel processing, high-efficiency, and practibility . Genetic Algorithms, based on the biological mechanism of natural selection & heredity and leveraging colony searching technology, is particularly applicable for the resolution of complicated & non-linear problems intractable with traditional searching methods.With the increment of population's evolve algebraic increasing, the average of fitness will be increasing frequently. Choosing a individual from two close population random, the difference of those two populations will be leading to the direction of the population's development. Therefore it could construct a new cross operator by making use of two close populations. A new individual will be made, and it will be frequently close to the optimal solution.The intergenerational differential genetic algorithms is suggested to optimize its search matching speed, and the whole process implementing the algorithm is elaborated.Intergenerational differential cross operator is one of the most important genetic algorithms'operator. It is designed to improve the fitness of individuals by means of combining traditional crossover operators with a new optimization technique, as well as a modified fitness function.In order to optimize the way of fractal encoding, this paper is to describe the research of a way about compression technologies of the fingerprint based on IDCO[1]. This arithmetic can improve the velocity and the accuracy rate.This paper proposes a novel genetic algorithms for fingerprint identification based on the intergenerational differential genetic algorithms. This means not only shortenning time in identifying procedure, but also ensuring a prominent improvement on the accuracy.