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Fingerprint Singular Point Detection Based on Multiple-Scale Orientation Entropy
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DOI：10.1109/LSP.2011.2169957.png)
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Abstract
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This letter develops a novel method for fingerprint singular point detection based on a new singularity representation of ridge-valley region called orientation entropy. The candidate singular point is obtained by the multiple-scale analysis of orientation entropy and some post processing steps are proposed to filter the spurious core and delta points. An iteration compensation scheme is proposed to search the precise location for core points against the offset further. Performance of the proposed method has been evaluated on the dataset of FVC2002 DB1. Experimental results show that the multiple-scale orientation entropy is correct and effective for singular detection and the location compensation scheme reduces the distance between the detection result and the truth singular point.
Keywords:
Entropy
multiple-scale analysis
orientation field
orientation field flow curve
singular point detection
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