Partial fingerprint identification through checkerboard sampling method using ANN

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

IEEE Region 10 Annual International Conference, Proceedings/TENCON

Publication Date

12-1-2012

Abstract

This paper presents a straightforward method of fingerprint identification considering partial fingerprints through neural network system. The fingerprint templates constitute the largest data in the biometric field. By considering partial fingerprint samples, the amount of data in the database shall be decreased and this will consequently lead to a faster processing for fingerprint identification. To address the problem on database capacity, sampling the full fingerprint is done through checkerboard algorithm. A standard 8×8 checkerboard is adopted wherein selected blocks are considered as samples for Artificial Neural Network (ANN) training. This will reduce the memory size of a fingerprint template to 50%. Also, 25% of the whole fingerprint is done to further reduce the memory size. The fingerprint images underwent the usual image enhancement by FFT and histogram equalization. Then, image binarization is done to be able to use pattern identification tool in an artificial neural network system available in MATLAB. © 2012 IEEE.

html

Digitial Object Identifier (DOI)

10.1109/TENCON.2012.6412170

Disciplines

Electrical and Computer Engineering | Electrical and Electronics

Keywords

Neural networks (Computer science); Information storage and retrieval systems—Fingerprints; Fourier transformations

Upload File

wf_no

This document is currently not available here.

Share

COinS