Fingerprint registration by maximization of mutual information.

Full Abstract

Fingerprint registration is a critical step in fingerprint matching. Although a variety of registration alignment algorithms have been proposed, accurate fingerprint registration remains an unresolved problem. We propose a new algorithm for fingerprint registration using orientation field. This algorithm finds the correct alignment by maximization of mutual information between features extracted from orientation fields of template and input fingerprint images. Orientation field, representing the flow of ridges, is a relatively stable global feature of fingerprint images. This method uses the statistics and distribution of global feature of fingerprint images so that it is robust to image quality and local changes in images. The primary characteristic of this method is that it uses this stable global feature to align fingerprints, and that its behavior may resemble the way humans compare fingerprints. Experimental results show that the occurrence of misalignment is dramatically reduced and that registration accuracy is greatly improved at the same time, leading to enhanced matching performance.

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Author information

Author/s: Liu, Lifeng (L); Jiang, Tianzi (T); Yang, Jianwei (J); Zhu, Chaozhe (C);

Affiliation: National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China. lliu(-atsign-)ucalgary.ca

Journal and publication information

Publication Type: Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't

Journal: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society (IEEE Trans Image Process), published in United States. (Language: eng)

Reference: 2006-May; vol 15 (issue 5) : pp 1100-10

Dates: Created 2006/05/04; Completed 2006/06/01; Revised 2006/11/15;

PMID: 16671291, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Algorithms
Artificial Intelligence
Dermatoglyphics
Fingers - anatomy & histology
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods

Information Storage and Retrieval - methods
Likelihood Functions
Pattern Recognition, Automated - methods
Reproducibility of Results
Sensitivity and Specificity
Skin - anatomy & histology
Subtraction Technique

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