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Fingerprint images vary in quality. In order to ensure that the performance of an automatic fingerprint identification system (AFIS) will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement module in the AFIS system. We introduce a new fingerprint enhancement algorithm which decomposes the input fingerprint image into a set of filtered images. From the filtered images, the orientation field is estimated and a quality mask which distinguishes the recoverable and unrecoverable corrupted regions in the input image is generated. The input fingerprint image is adaptively enhanced in the recoverable regions. The performance of our algorithm has been evaluated on an online fingerprint verification system using the MSU fingerprint database containing over 600 fingerprint images. Experimental results show that our enhancement algorithm improves the performance of the online fingerprint verification system and makes it more robust with respect to the quality of input fingerprint images.
Hong et al. (Tue,) studied this question.
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