Contactless fingerprint recognition: A neural approach for perspective and rotation effects reduction

Abstract

Abstract-Contactless fingerprint recognition systems are being researched in order to reduce intrinsic limitations of traditional biometric acquisition technologies, encompassing the release of latent fingerprints on the sensor platen, non-linear spatial distortions in the captured samples, and relevant image differences with respect to the moisture level and pressure of the fingertip on the sensor surface.Fingerprint images captured by single cameras, however, can be affected by perspective distortions and deformations due to incorrect alignments of the finger with respect to the camera optical axis. These non-idealities can modify the ridge pattern and reduce the visibility of the fingerprint details, thus decreasing the recognition accuracy. Some systems in the literature overcome this problem by computing three-dimensional models of the finger. Unfortunately, such approaches are usually based on complex and expensive acquisition setups, which limit their portability in consumer devices like mobile phones and tablets.In this paper, we present a novel approach able to recover perspective deformations and improper fingertip alignments in single camera systems. The approach estimates the orientation difference between two contactless fingerprint acquisitions by using neural networks, and permits to register the considered samples by applying the estimated rotation angle to a synthetic three-dimensional model of the finger surface. The generalization capability of neural networks offers a significant advantage by allowing processing a robust estimation of the orientation difference with a very limited need of computational resources with respect to traditional techniques. Experimental results show that the approach is feasible and can effectively enhance the recognition accuracy of single-camera biometric systems. On the evaluated dataset of 800 contactless images, the proposed method permitted to decrease the equal error rate of the used biometric system from 3.04% to 2.20%.

Accurate 3D fingerprint virtual environment for biometric technology evaluations and experiment design

“…The multiple view acquisitions have been simulated using the method described in section III-E, and the three-dimensional reconstruction procedure and unwrapping method described in [7] have been applied. Then, the unwrapped images have been enhanced using the method described in [17] in order to compute the contact-equivalent acquisitions. The obtained images have then been processed by using the minutiae extraction software NIST MINDTCT [20], designed for contact-based images.…”

“…The method is based on the technique described in [17] and computes a parametric finger shape based on fourth-order polynomials. The parametric model has been designed by studying three-dimensional models computed from real acquisitions [7], and permits to create synthetic three-dimensional shape in a simple and accurate manner.…”

The biometric recognition on contactless multi-spectrum finger images

“…1. According to previous research, fingerprints acquired with a contact system present better contrast between ridges and valleys than those acquired with contactless systems [19]. Hence, the minutiae-extraction method used with contact fingerprint images is not suitable for the blurred contactless fingerprint images.…”

Toward Unconstrained Fingerprint Recognition: A Fully Touchless 3-D System Based on Two Views on the Move

“…Therefore, most biometric systems use guides to place the body part. A few studies on techniques that do not use placement guides have been performed on traits such as fingerprints [25]- [27], hand surface [7], and finger shape [28]. Studies of fingerprint recognition with movement have been limited to 2-D acquisitions [29].…”

“…First, we propose an innovative acquisition setup and new processing algorithms that introduce important novelties compared with previous studies [25], [36]. Second, we present direct comparisons between the proposed fully touchless systems, touchless approaches in the literature, and touch-based technologies.…”