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Mathematical Morphology Approach for Genuine Fingerprint Feature Extraction.
Vikas Humbe, S. S. Gornale, Ramesh Manza, K. V. Kale
Pages - 45 - 51     |    Revised - 15-08-2007     |    Published - 30-08-2007
Volume - 1   Issue - 2    |    Publication Date - August 2007  Table of Contents
Feature Extraction, Morphology, Fingerprints, superfluous information etc
Recognition systems based on biometrics (faces, hand shapes and fingerprints etc.) are finally taking off although it has taken a long way to come. Fingerprints have been a precious tool for law enforcement, forensics and recently in commercial use for over a century. Evaluate the performance of these emerging technologies is tricky problem. Most fingerprint verification algorithms rely on minutiae features, and these algorithms can only be as robust as the underlying minutiae features. Therefore, reliable minutiae extraction is vital to a system’s performance. Most of the feature extraction techniques extract features from thinned images but while dealing with binarization and skeletization of image it introduces noise or superfluous information, which creates troubles for genuine feature extraction. In this paper we have used the mathematical morphology to remove the superfluous information for genuine feature extraction and measure the feature extraction performance through sensitivity and specificity.
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Mr. Vikas Humbe
- India
Mr. S. S. Gornale
- India
Mr. Ramesh Manza
- India
Mr. K. V. Kale
- India