Fingerprint Database Optimization Using Watershed Transformation Algorithm


Fingerprints are a unique feature for identification and verification of humans. The need to optimise several databases for storing the images of fingerprints is a major concerning issue. Several segmentation algorithms have been used in the time past but there are still several challenges facing some current segmentation algorithms like computational efficiency. Another challenge is that segmentation procedure can be impractically slow, or requires extremely large amounts of memory. This paper addresses the challenges by employing watershed flooding algorithm on the fingerprint images so as to optimize the sizes of the databases. A pre-processing plug-in that implements this segmentation process is developed using Java. We showed its effectiveness by testing it on fingerprint image dataset and the entropy showed that the segmented images sizes were reduced.

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Kolade, O. , Olayinka, A. and Ovie, U. (2014) Fingerprint Database Optimization Using Watershed Transformation Algorithm. Open Journal of Optimization, 3, 59-67. doi: 10.4236/ojop.2014.34006.

Conflicts of Interest

The authors declare no conflicts of interest.


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