Semi-automatic progressive enhancement for latent fingerprints

摘要

We propose a semi-automatic progressive enhancement method for latent fingerprints. This method requires three inputs; a latent image, a manual segmentation, and an initial block location. The method starts enhancing the initial block using a matched filter in the frequency domain, then the enhanced block is padded back on the input latent image. The padded image is fed back as an input image and the surrounding blocks of the enhanced block are progressively enhanced. The proposed method performs iterative enhancement and feedback until the enhanced blocks fill the entire segmentation. The proposed method is benchmarked against several state-of-the-art methods with the NIST SD27 database. The experimental results show that the proposed method outperforms other methods in terms of identification accuracy.