The Research Of Fingerprint Classification Based On Genetic Algorithm

Fingerprint classification(FC) which has been the hot point and hard point of researchers in national or aboard is an important composing of Automatic Fingerprint Recognition System(AFRS). In the research of AFRS, FC provides an important reference mechanism making very important sense. With the fingerprint classification, it can exclude fingerprint of the different class. As a nicety and coherent classification can observably reduce the matching time of huge fingerprint database, designing a FC system with great capability will enormously improve the use efficiency of the AFRS and the store of character data and searches of database will be more convenient.Genetic Algorithm(GA) which simulates the processes of biological evolution possesses some outstanding characters, such as kicking over the traces of confine, implicit parallelism and global searching ability. GA which independent of the idiographic filed of problems, provide a common frame to solve the optimize of complex system. GA used in a lot of subject because of it has a strong quality of rush-stick.After introducing the FC and GA, a FC algorithm based on GA which is consist of a improved GA and the basic FC algorithm based on GA was designed. At the same time, a two-level FC strategy which observably improves the efficiency of FC is constructed. The main contributions of this thesis can be summarized as follows:1. After reviewing the FC algorithm in national and aboard and comparing the different FC algorithm, the topic of our research is bringing forward.2. An improvement of the born classification is designed by adding a joined BP operator GA.3. Based on the analysis of FC, a two-level FC is designed.