Level 2 feature extraction for latent fingerprint enhancement and matching using type-2 intuitionistic fuzzy set

Abstract

Latent fingerprints are acquired from crime places which are utilised to distinguish suspects in crime inspection. In general, latent fingerprints contain mysterious ridge and valley structure with nonlinear distortion and complex background noise. These lead to fundamentally difficult problem for further analysis. Hence, the image quality is required for matching those latent fingerprints. In this work, we develop a model, which needs manually marked region of interest latent fingerprints for enhancement and matching. The proposed model includes two phases: i) latent fingerprints contrast enhancement using intuitionistic fuzzy set; ii) extract the level 2 feature (minutiae) from the latent fingerprint image. This technique is functioned depend on minutia points which investigate n number of images and the Euclidean distance is applied for calculate the matching scores. We tested our algorithm for matching, using some public domain fingerprint databases such as fingerprint verification competition-2004 and Indraprastha Institute of Information Technology-latent fingerprint, which indicates that by fusing the proposed enhancement algorithm, the matching precision has fundamentally, moved forward.