Latent Fingerprint Core Point Prediction Based on Gaussian Processes

Core point prediction is of critical importance to latent fingerprints individuality assessment. While tremendous effort have been made in core point detection, locating core points in latent fingerprints continues to be a difficult problem because latent prints usually contain only partial images with core points left outside the print. A novel method is proposed that predicts the locations and orientations of core points for latent fingerprints. The method is based on Gaussian processes and provides prediction in interpretations of probability rather than binary decision. The accuracy of the method is illustrated by experiments on a real-life latent fingerprint data set.