Global Ridge Orientation Modeling for Partial Fingerprint Identification

Abstract

Abstract-Identifying incomplete or partial fingerprints from a large fingerprint database remains a difficult challenge today. Existing studies on partial fingerprints focus on one-to-one matching using local ridge details. In this paper, we investigate the problem of retrieving candidate lists for matching partial fingerprints by exploiting global topological features. Specifically, we propose an analytical approach for reconstructing the global topology representation from a partial fingerprint. Firstly, we present an inverse orientation model for describing the reconstruction problem. Then, we provide a general expression for all valid solutions to the inverse model. This allows us to preserve data fidelity in the existing segments while exploring missing structures in the unknown parts. We have further developed algorithms for estimating the missing orientation structures based on some a priori knowledge of ridge topology features. Our statistical experiments show that our proposed model-based approach can effectively reduce the number of candidates for pair-wised fingerprint matching, and thus significantly improve the system retrieval performance for partial fingerprint identification.

An Advanced Latent Fingerprint Matching by Using Level Three Features

“…These include singular points and pattern type [3], ridge flow map (or orientation field) , ridge wavelength map (or frequency map) [4,5], skeleton , and crease [6]. However, these studies primarily address full fingerprint matching and, to our knowledge, there is no published algorithm on using extended features for latent matching.…”

Design & Implementation of Fingerprint Biometrics based on Discretized Fingerprint Texture Descriptor

“…The image area without operative ridges and furrows is first discarded since it only holds background information. Then bound of remaining effective area is sketched out since the minutia in bound region are confusing with those spurious minutia that are generated when the ridges are out of the sensor [9].…”

Design & Implementation of Adaptive Fingerprint Biometrics with Training of DataSet

“…Thus, they had concluded that the proposed ridge feature gave additional information for fingerprint matching with little increment in template size and used in conjunction with existing minutiae features to increase the accuracy and robustness of fingerprint recognition systems. Some [9] presented an investigation of the problem of retrieving candidate lists for matching partial fingerprints by exploiting global topological features. They proposed an analytical approach for reconstructing the global topology representation from a partial fingerprint.…”