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Fingerprint recognition is a widely used biometric identification mechanism. In case of correlation based fingerprint recognition detection of a consistent registration point is a crucial issue; this point can be a core point of a fingerprint. Many techniques have been proposed but success rate is highly dependent on input used and accurate core point detection is still an open issue. Here, the authors discuss an algorithm which is based on multiple features derived from the fingerprint which are collectively used for consistent core point detection. Here, they use Orientation field, coherence, Poincare index for core point detection. Though all fingerprints don't possess core point still this algorithm is useful to detect high curvature regions and gives high accuracy as it combines advantages form individual features.
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