An efficient cascaded system for latent fingerprint recognition

Abstract

This paper proposes a cascaded scheme to improve the efficiency of latent fingerprint identification system. In this scheme, the feature set of latent fingerprint such as finger codes, basic patterns, ridge counts and minutia with their local structures are sequentially exploited in four cascaded layers. In the first layer, possible finger codes of latent fingerprint are recognized based on basic pattern features and then reordered to determine their database access priority. In the second layer, its minutiae are extracted and assessed to affine matching in the third layer. In the fourth layer, any case having too many candidates in the previous layer is further matched based on exploiting local structure in order to downsizing the result list. On the verification layer, the minutiae information and local structure of corresponding pairs are presented to human experts for further verification. Experimental results on C@FRIS database show that our proposed method obtains high matching accuracy and considerably low identification time.