750 IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 5, NO. 4, DECEMBER 2010 Data Acquisition and Processing of 3-D Fingerprints Yongchang Wang, Member, IEEE, Laurence G. Hassebrook, Senior Member, IEEE, and Daniel L. Lau, Senior Member, IEEE Abstract—To solve the problems associated with conventional 2-D fingerprint scanners such as skin deformation and print smearing, in this paper we introduce a noncontact fingerprint scanner employing structured light illumination to generate high-resolution albedo images as well as 3-D ridge scans. The question to be answered in this research is whether or not ridge depth information improves the quality and matching capability of acquired fingerprints? For evaluation of this question, we use the National Institute of Standards and Technology fingerprint image quality metrics. These metrics require the 3-D prints to be flattened. We present a complete and detailed flattening algorithm based upon unfolding an elastic tube fit to the peaks and valleys of ridges identified within the scan. Further improvement of the flattened print is achieved through the incorporation of ridge information extracted from the albedo image with the depth and albedo ridge information fused together according to local scan quality. Our study compares image quality between the flattened 3-D prints and ink rolled prints. Most significantly, the matching performance of 3-D flattened to 3-D flattened prints is evaluated based on ridge depth only, albedo only, and depth with albedo fusion. Index Terms—Albedo, depth, flatten, fuse, 3-D fingerprint. I. INTRODUCTION AND PREVIOUS WORKS F INGERPRINTS, due to their uniqueness and im- mutability, have been applied to identify criminals in law enforcement and, currently, are increasingly being used for personal identification in civilian applications [1]–[4]. Systems for automating fingerprint matching are generally described in terms of data acquisition, postprocessing, and registration [5], [6]. Among these three parts, data acquisition is gener- ally regarded as the most critical because of its great effect on overall system performance [5]. Traditionally, fingerprint images are acquired by pressing or rolling a finger against a hard surface (e.g., glass, silicon, polymer) or paper (e.g., index card). Aside from obligatory maintenance of the sensor/prism surface, these contact-based scanners often result in partial or degraded images [7]–[13], due to: Manuscript received August 31, 2009; revised June 23, 2010; accepted June 29, 2010. Date of publication July 29, 2010; date of current version November 17, 2010. This work was supported in part by Flashscan3D, LLC, Richardson, TX and in part by the National Institute of Hometown Security, Somerset, KY. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Arun Ross. Y. Wang and D. L. Lau are with the Center for Visualization and Virtual Environments, University of Kentucky, Lexington, KY 40507 USA (e-mail: ywang6@engr.uky.edu; lgh@engr.uky.edu). L. G. Hassebrook is with the Center for Visualization and Virtual Environ- ments, University of Kentucky, Lexington, KY 40507 USA, and also with Flash- scan3D, LLC, Richardson, TX 75080 USA (e-mail: dllau@engr.uky.edu). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TIFS.2010.2062177 1) uncontrollability and nonuniformity of the finger pressure on the device; 2) permanent or semipermanent change of the finger ridge structure due to injuries or heavy manual labor; 3) residue from the previous fingerprint capture; 4) data distortion under different illumination, environmental, and finger skin conditions; 5) loss of surrounding information in technologies without finger rolling; and 6) extra scanning time and motion artifacts incurred in tech- nologies that require finger rolling. The majority of these limitations arise due to the physical contact of the finger surface with the sensor plate, or the non- linear distortion introduced by the 3-D to 2-D mapping during image acquisition [14]. To eliminate the many drawbacks of contact-based scanning, several novel technologies have been developed [15]–[19] that avoid direct contact between the sensor and the skin, and thus, consistently preserve the fingerprints “ground-truth” without skin deformation during acquisition [20]. In [17] and [18], Parziale et al. proposed a multicamera touchless fingerprint scanner which acquires different finger views that are combined together to provide a 3-D representation of the fingerprint. Due to the lack of contact between the elastic skin of the finger and any rigid surface, the acquired images present little deformation [18]. However, based on the shape-from-silhouette scanning technique, the 3-D ridge information cannot be obtained, and the ridge information is obtained from the surface reflection variation (i.e., albedo) information. Thus, the fingerprint is affected by surface color, surface reflectance, geometric factors and other effects. In this paper, we employ a noncontact, 3-D scanning method of structured light illumination (SLI) through phase measuring profilometry (PMP) [21]–[23] to make a 3-D scan of the human finger with sufficiently high resolution so as to record 3-D ridge- depth information. Compared to other structure light algorithms like De Bruijn sequences [24], binary codes [25], or gray levels projection [26], the PMP technique exploits higher spatial res- olution [27], which can achieve a given precision with fewer frames. Now because our scanner captures fingerprint ridges and val- leys as they contour a cylindrically shaped finger, corresponding fingerprints must be virtually flattened in order to be backwards compatible with existing recognition/matching systems, which have evolved around contact-based scanning. In general, the flattening problem has been studied by cartographers, like Ger- ardus Mercator, for hundreds of years and is well known as the map projection problem [28], [29]. A map projection refers to any method of representing the surface of a sphere or other shape on a plane [30], [31]. Besides globe unwrapping which 1556-6013/$26.00 © 2010 IEEE