Abstract: Various examples are provided for distortion rectification and fingerprint crossmatching. In one example, a method includes selecting an electronic, perspective distorted fingerprint sample; and generating an unwarped fingerprint sample by rectifying perspective distortions from the perspective distorted fingerprint sample by application of an unwarping transformation. Parameters of the unwarping transformation can be determined by a deep convolutional neural network (DCNN) trained on a database comprising contactless fingerprint samples suffering from perspective distortions.

Abstract: Various examples are provided related to fingerphoto deblurring. In one example, a method includes generating, using a guided-attention (GA) mechanism, an intermediate feature map of a blurred image of a fingerprint and generating a deblurred image of the fingerprint based at least in part upon the intermediate feature map. The GA mechanism can generate the intermediate feature map by generating an attended feature map from an input feature map based upon a predicted attention map and adding the input feature map to the attended feature map. A system can include processing circuitry and a fingerphoto deblurring application that, when executed by the processing circuitry, causes the processing circuitry to generate the intermediate feature map and generate the deblurred image.

Abstract: Various examples are provided for distortion rectification and fingerprint crossmatching. In one example, a method includes selecting an electronic, perspective distorted fingerprint sample; and generating an unwarped fingerprint sample by rectifying perspective distortions from the perspective distorted fingerprint sample by application of an unwarping transformation. Parameters of the unwarping transformation can be determined by a deep convolutional neural network (DCNN) trained on a database comprising contactless fingerprint samples suffering from perspective distortions.

Abstract: Various examples are provided for fingerprint distortion rectification. In one example, a method includes selecting a geometrically distorted fingerprint sample and generating a rectified fingerprint sample by rectifying geometric distortions from the geometrically distorted fingerprint sample by application of an estimated distortion field determined by a deep convolutional neural network (DCNN) trained previously on a database of synthetic, geometrically distorted fingerprint samples.