Neural Network Based Automatic Fingerprints Classification Algorithm

Author

Li Xiangrong ; Wang Guohui ; Lu Xiangjiang

Author_Institution

Dept. of Arms Eng., Acad. of Armored Force Eng., Beijing, China

Volume

1

fYear

2010

fDate

7-8 Aug. 2010

Firstpage

94

Lastpage

96

Abstract

It Presented one neural network based automatic fingerprints classification algorithm. Fingerprint features extracted through resolving directed graph are input into neural network to be classified. Weight coefficients of network connection are studied and optimized based on the genetic algorithm. Test results show that its performance is excellent and the total accurate classification rate reaches up to 93.12%. Research in the paper is significant to fingerprint identifications applied in large-scale information security authentication systems such as bank saving network system and network exchange system.

Keywords

banking; directed graphs; feature extraction; fingerprint identification; genetic algorithms; message authentication; neural nets; pattern classification; automatic fingerprints classification algorithm; bank saving network system; directed graph; fingerprint features extraction; genetic algorithm; large-scale information security authentication systems; network connection weight coefficients; network exchange system; neural network; Algorithm design and analysis; Artificial neural networks; Classification algorithms; Feature extraction; Fingerprint recognition; Image matching; Information security; automatic classification algorithm; fingerprint identification; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Management Engineering (ISME), 2010 International Conference of

Conference_Location

Xi´an

Print_ISBN

978-1-4244-7669-5

Electronic_ISBN

978-1-4244-7670-1

Type

conf

DOI

10.1109/ISME.2010.187

Filename

5573753