Model Based Separation of Overlapping Latent Fingerprints
Latent fingerprints lifted from crime scenes often contain overlapping prints, which are difficult to separate and match by state-of-the-art fingerprint matchers. A few methods have been proposed to separate overlapping fingerprints to enable fingerprint matchers to successfully match the component fingerprints. These methods are limited by the accuracy of the estimated orientation field, which is not reliable for poor quality overlapping latent fingerprints. In this paper, the authors improve the robustness of overlapping fingerprints separation, particularly for low quality images. Their algorithm reconstructs the orientation fields of component prints by modeling fingerprint orientation fields.