Improving the Accuracy of Latent Fingerprint Matching Using Texture Descriptors

Fingerprint matching is a process used to check whether two sets of fingerprint come from the same finger of a person. There are three types of fingerprints in law enforcement applications such as rolled, plain, and latent. Latent fingerprints are partial fingerprint, obtained from the surfaces of objects where a person has touched. It may or may not be an accidental touch. Latent fingerprint contains small area of prints as compared to full fingerprints. We cannot apply a full fingerprint matching algorithm for the latent fingerprint matching. Matching between a latent and a rolled print is a complex task because the number of minutia points will be less. Enhancement of fingerprint is necessary due to low quality of latents and sensor noise. We have done latent fingerprint matching using Hough transform algorithm. Experimental results on NIST latent fingerprint database show an accuracy of 54.43 %. We have enhanced the accuracy by incorporating texture-based features like entropy, correlation, contrast, homogeneity, and energy.