Abstract
An important step in automatic fingerprint recognition systems is the segmentation of fingerprint images. In this paper, we present an adaptive algorithm based on Gaussian-Hermite moments for non-uniform background removing in fingerprint image segmentation. Gaussian-Hermite moments can better separate image features based on different modes. We use Gaussian-Hermite moments of different orders to separate background and foreground of fingerprint image. In order to further improve the segmentation result, morphology is applied as postprocessing to removing small areas and filling small interior holes. Experimental results show that the use of Gaussian-Hermite moments makes a significant improvement in fingerprint image segmentation performance.
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