Reference point detection for camera-based fingerprint image based on wavelet transformation

Abstract

BackgroundFingerprint recognition systems essentially require core-point detection prior to fingerprint matching. The core-point is used as a reference point to align the fingerprint with a template database. When processing a larger fingerprint database, it is necessary to consider the core-point during feature extraction. Numerous core-point detection methods are available and have been reported in the literature. However, these methods are generally applied to scanner-based images. Hence, this paper attempts to explore the feasibility of applying a core-point detection method to a fingerprint image obtained using a camera phone.MethodThe proposed method utilizes a discrete wavelet transform to extract the ridge information from a color image. The performance of proposed method is evaluated in terms of accuracy and consistency. These two indicators are calculated automatically by comparing the method’s output with the defined core points.ResultsThe proposed method is tested on two data sets, controlled and uncontrolled environment, collected from 13 different subjects. In the controlled environment, the proposed method achieved a detection rate 82.98%. In uncontrolled environment, the proposed method yield a detection rate of 78.21%.ConclusionThe proposed method yields promising results in a collected-image database. Moreover, the proposed method outperformed compare to existing method.

An accurate fingerprint reference point determination method based on curvature estimation of separated ridges

“…The reference point is employed in those fingerprint comparison techniques where the given template and an unknown fingerprint image have to be matched. It should be noted that a large number of classification and matching algorithms can be used for such operations (Galar et al, 2015;Bo et al, 2008;Jain et al, 2000;Porwik and Wieclaw, 2004;Khalil, 2015;Xie and Zhang, 2016;Weng et al, 2011;Gavrilova and Monwar, 2013).…”

“…Unfortunately, an OM may generate too many singular points such that some are detected incorrectly. Other methods use techniques based on Poincaré index determinations, or friction ridges masks, and many other aforementioned techniques that incorporate dedicated approaches based on heuristic image processing techniques (Porwik and Wieclaw, 2004;Khalil, 2015;Le and Van, 2012;Arjona et al, 2011;Wang et al, 2007).…”

“…The author of the reference point localization work, Khalil (2015), proposed an algorithm based on a discrete wavelet transform. While this is very productive method, the author's camera images had some illumination problems due to the use of several lighting sources.…”

Improved Hessian Curvature for Fingerprint Analysis

“…And also, the proposed method was compared with the complex filtering method proposed by A.K. Jain et al [7][8] on the spatial and frequency domain [9]. Curvature analysis is meaningful to the fingerprint authentication [10].…”

Beam Search Algorithm for Fingerprint Reference Point Determination Based on Joint Orientation Features

“…Jain et al [8] determine a reference point using the multi-resolution analysis of the differences of sine component integration between any two regions in the orientation filed. And also the complex filtering methods [9,10] detect the maximum curvature based on the ridge orientation field. However these methods still can't perform well for the plain arch type fingerprint.…”