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An improved O'Gorman filter for fingerprint image enhancement

In fingerprint recognition the performance of the minutiae extraction is completely rely on the quality of an image. The image enhancement is a very important phase in fingerprint recognition for improving the image quality by removing the noise and by connecting the broken ridges. Most of the fingerprint image enhancement algorithms are mainly constructed using the contextual filters. Gabor Filter and O'Gorman filters are the well-known contextual filter among them. This paper shows the implementation work of both algorithms as well as doing the enhancement in O'Gorman Filter. The implementation work done in java platform using fingerprint databases FVC2000 and FingerDos. The performance of Gabor Filter, O'Gorman Filter and enhanced O'Gorman Filter is compared using standard like Mean Square Error, Peak Signal Noise Ratio and with computational time.