Fingerprint recognition using fuzzy artmap neural network architecture

Author

Dagher, Issam ; Helwe, Wael ; Yassine, Firass

Author_Institution

Dept. of Comput. Eng., Balamand Univ., El Koura, Lebanon

fYear

2002

fDate

11-13 Dec. 2002

Firstpage

157

Lastpage

160

Abstract

In this paper, a neural network architecture, Fuzzy Artmap (FAM), was used to classify fingerprints. A fingerprint database of the University of Balamand (UOB) was created. The algorithm uses the filterbank representation which captures the local and global details in a fingerprint as a 320-byte fixed length FingerCode which is suitable for storage. In the first stage, the fingerprint is classified using FAM to one of the five categories (whorl, left loop, right loop, arch, and tented arch). Then, the algorithm matches the fingerprint by searching in the specific category in the database. Matching is done using the two corresponding FingerCodes and thus, is very fast.

Keywords

feature extraction; fingerprint identification; fuzzy neural nets; image classification; image matching; neural net architecture; 320 bytes; FAM; UOB; University of Balamand; arch; filterbank representation; fingerprint database; fingerprint matching; fingerprint recognition; fixed length fingercode; fuzzy artmap; left loop; neural network architecture; right loop; tented arch; whorl; Authentication; Biometrics; Computer architecture; Fingerprint recognition; Frequency; Fuzzy neural networks; Image databases; Image matching; Neural networks; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Microelectronics, The 14th International Conference on 2002 - ICM

Print_ISBN

0-7803-7573-4

Type

conf

DOI

10.1109/ICM-02.2002.1161519

Filename

1161519