Soft information fusion of correlation filter output planes using support vector machines for improved fingerprint verification performance

Krithika Venkataramani*, Mehmet Keskinoz, B. V.K.Vijaya Kumar

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

Reliable verification and identification can be achieved by fusing hard and soft information from multiple classifiers. Correlation filter based classifiers have shown good performance in biometric verification applications. In this paper, we develop a method of fusing soft information from multiple correlation filters. Usually, correlation filters are designed to produce a strong peak in the correlation filter output for authentics whereas no such peak should be produced for impostors. Traditionally, the peak-to-sidelobe-ratio (PSR) has been used to characterize the strength of the peak and thresholds are set on the PSR in order to determine whether the test image is an authentic or an impostor. In this paper, we propose to fuse multiple correlation output planes, by appending them for classification by a Support Vector Machine (SVM), to improve the performance over traditional PSR based classification. Multiple Unconstrained Optimal Tradeoff Synthetic Discriminant Function (UOTSDF) filters having varying degrees of discrimination and distortion tolerance are employed here to create a feature vector for classification by a SVM, and this idea is evaluated on the plastic distortion set of the NIST 24 fingerprint database. Results on this database provide an Equal Error Rate (EER) of 1.36% when we fuse correlation planes, in comparison to an average EER of 3.24% using the traditional PSR based classification from a filter, and 2.4% EER on fusion of PSR scores from the same filters using SVM, which demonstrates the advantages of fusing the correlation output planes over the fusion of just the peak-to-sidelobe-ratios (PSRs).

Original languageEnglish
Article number22
Pages (from-to)184-195
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5779
DOIs
Publication statusPublished - 2005
Externally publishedYes
EventBiometric Technology for Human Identification II - Orlando, FL, United States
Duration: 28 Mar 200529 Mar 2005

Keywords

  • Correlation filters
  • Fingerprint verification
  • Fusion
  • Support Vector Machines

Fingerprint

Dive into the research topics of 'Soft information fusion of correlation filter output planes using support vector machines for improved fingerprint verification performance'. Together they form a unique fingerprint.

Cite this