Please use this identifier to cite or link to this item:
Title: Fingerprint recognition using fuzzy artmap neural network architecture
Authors: Dagher, Issam 
Helwe, W
Yassine, F.
Affiliations: Department of Computer Engineering 
Keywords: Neural net architecture
Feature extraction
Image matching
Image classification
Fuzzy neural nets
Subjects: Fingerprints--Identification
Issue Date: 2003
Publisher: IEEE
Part of: The 14th International Conference on Microelectronics
Start page: 157
End page: 160
Conference: International Conference on Microelectronics (ICM) (14th : 13 Dec 2002 : Beirut, Lebanon) 
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.
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Computer Engineering

Show full item record

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.