Showing papers on "Fingerprint recognition published in 2010"

Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition

Abstract: In this paper, we introduce the Minutia Cylinder-Code (MCC): a novel representation based on 3D data structures (called cylinders), built from minutiae distances and angles. The cylinders can be created starting from a subset of the mandatory features (minutiae position and direction) defined by standards like ISO/IEC 19794-2 (2005). Thanks to the cylinder invariance, fixed-length, and bit-oriented coding, some simple but very effective metrics can be defined to compute local similarities and to consolidate them into a global score. Extensive experiments over FVC2006 databases prove the superiority of MCC with respect to three well-known techniques and demonstrate the feasibility of obtaining a very effective (and interoperable) fingerprint recognition implementation for light architectures.

Fingerprint Matching

Abstract: Fingerprint matching has been successfully used by law enforcement for more than a century. The technology is now finding many other applications such as identity management and access control. The authors describe an automated fingerprint recognition system and identify key challenges and research opportunities in the field.

The Biometric Menagerie

Abstract: It is commonly accepted that users of a biometric system may have differing degrees of accuracy within the system. Some people may have trouble authenticating, while others may be particularly vulnerable to impersonation. Goats, wolves, and lambs are labels commonly applied to these problem users. These user types are defined in terms of verification performance when users are matched against themselves (goats) or when matched against others (lambs and wolves). The relationship between a user's genuine and impostor match results suggests four new user groups: worms, doves, chameleons, and phantoms. We establish formal definitions for these animals and a statistical test for their existence. A thorough investigation is conducted using a broad range of biometric modalities, including 2D and 3D faces, fingerprints, iris, speech, and keystroke dynamics. Patterns that emerge from the results expose novel, important, and encouraging insights into the nature of biometric match results. A new framework for the evaluation of biometric systems based on the biometric menagerie, as opposed to collective statistics, is proposed.

Privacy-preserving fingercode authentication

Abstract: We present a privacy preserving protocol for fingerprint-based authentication. We consider a scenario where a client equipped with a fingerprint reader is interested into learning if the acquired fingerprint belongs to the database of authorized entities managed by a server. For security, it is required that the client does not learn anything on the database and the server should not get any information about the requested biometry and the outcome of the matching process. The proposed protocol follows a multi-party computation approach and makes extensive use of homomorphic encryption as underlying cryptographic primitive. To keep the protocol complexity as low as possible, a particular representation of fingerprint images, named Fingercode, is adopted. Although the previous works on privacy-preserving biometric identification focus on selecting the best matching identity in the database, our main solution is a generic identification protocol and it allows to select and report all the enrolled identities whose distance to the user's fingercode is under a given threshold. Variants for simple authentication purposes are provided. Our protocols gain a notable bandwidth saving (about 25-39%) if compared with the best previous work (ICISC'09) and its computational complexity is still low and suitable for practical applications. Moreover, even if such protocols are presented in the context of a fingerprint-based system, they can be generalized to any biometric system that shares the same matching methodology, namely distance computation and thresholding.

A hybrid biometric cryptosystem for securing fingerprint minutiae templates

Abstract: Security concerns regarding the stored biometric data is impeding the widespread public acceptance of biometric technology. Though a number of bio-crypto algorithms have been proposed, they have limited practical applicability due to the trade-off between recognition performance and security of the template. In this paper, we improve the recognition performance as well as the security of a fingerprint based biometric cryptosystem, called fingerprint fuzzy vault. We incorporate minutiae descriptors, which capture ridge orientation and frequency information in a minutia's neighborhood, in the vault construction using the fuzzy commitment approach. Experimental results show that with the use of minutiae descriptors, the fingerprint matching performance improves from an FAR of 0.7% to 0.01% at a GAR of 95% with some improvement in security as well. An analysis of security while considering two different attack scenarios is also presented. A preliminary version of this paper appeared in the International Conference on Pattern Recognition, 2008 and was selected as the Best Scientific Paper in the biometrics track.

Research on a Clustering Data De-Duplication Mechanism Based on Bloom Filter

Abstract: Recently, data de-duplication, the hot emerging technology, has received a broad attention from both academia and industry Some researches focus on the approach by which to reduce more redundant data And the others investigate how to do de-duplication at high speed In this paper, we aim at reducing the time and space requirement for data de-duplication We describe a clustering architecture with multiple nodes and all nodes can do the chunk-level data de-duplication in parallel Thus the performance will be improved noticeably At the same time, this paper proposes a new technique called "Fingerprint Summary" Each node keeps a compact summary of the chunks' fingerprints of every other node in its memory When checking for duplicate chunks, each node queries its local chunk hash database and then the Fingerprint Summary if necessary to eliminate inter-node redundant chunks So we can reduce the storage capacity requirement largely

A Frequency-based Approach for Features Fusion in Fingerprint and Iris Multimodal Biometric Identification Systems

Abstract: The basic aim of a biometric identification system is to discriminate automatically between subjects in a reliable and dependable way, according to a specific-target application. Multimodal biometric identification systems aim to fuse two or more physical or behavioral traits to provide optimal False Acceptance Rate (FAR) and False Rejection Rate (FRR), thus improving system accuracy and dependability. In this paper, an innovative multimodal biometric identification system based on iris and fingerprint traits is proposed. The paper is a state-of-the-art advancement of multibiometrics, offering an innovative perspective on features fusion. In greater detail, a frequency-based approach results in a homogeneous biometric vector, integrating iris and fingerprint data. Successively, a hamming-distance-based matching algorithm deals with the unified homogenous biometric vector. The proposed multimodal system achieves interesting results with several commonly used databases. For example, we have obtained an interesting working point with FAR = 0% and FRR = 5.71% using the entire fingerprint verification competition (FVC) 2002 DB2B database and a randomly extracted same-size subset of the BATH database. At the same time, considering the BATH database and the FVC2002 DB2A database, we have obtained a further interesting working point with FAR = 0% and FRR = 7.28% ÷ 9.7%.

Analysis of Fingerprint Pores for Vitality Detection

Abstract: Spoofing is an open-issue for fingerprint recognition systems. It consists in submitting an artificial fingerprint replica from a genuine user. Current sensors provide an image which is then processed as a “true” fingerprint. Recently, the so-called 3rd-level features, namely, pores, which are visible in high-definition fingerprint images, have been used for matching. In this paper, we propose to analyse pores location for characterizing the “liveness” of fingerprints. Experimental results on a large dataset of spoofed and live fingerprints show the benefits of the proposed approach.

Internal Fingerprint Identification With Optical Coherence Tomography

Abstract: Existing biometric fingerprint devices show numerous reliability problems such as wet or fake fingers. In this letter, a secured method using the internal structures of the finger (papillary layer) for fingerprint identification is presented. With a frequency-domain optical coherence tomography (FD-OCT) system, a 3-D image of a finger is acquired and the information of the internal fingerprint extracted. The right index fingers of 51 individuals were recorded three times. Using a commercial fingerprint identification program, 95% of internal fingerprint images were successfully recognized. These results demonstrate that OCT imaging of internal fingerprints can be used for accurate and reliable fingerprint recognition.

Data Acquisition and Processing of 3-D Fingerprints

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.

Managing a Large Database of Camera Fingerprints

Abstract: Sensor fingerprint is a unique noise-like pattern caused by slightly varying pixel dimensions and inhomogeneity of the silicon wafer from which the sensor is made. The fingerprint can be used to prove that an image came from a specific digital camera. The presence of a camera fingerprint in an image is usually established using a detector that evaluates cross-correlation between the fingerprint and image noise. The complexity of the detector is thus proportional to the number of pixels in the image. Although computing the detector statistic for a few megapixel image takes several seconds on a single-processor PC, the processing time becomes impractically large if a sizeable database of camera fingerprints needs to be searched through. In this paper, we present a fast searching algorithm that utilizes special "fingerprint digests" and sparse data structures to address several tasks that forensic analysts will find useful when deploying camera identification from fingerprints in practice. In particular, we develop fast algorithms for finding if a given fingerprint already resides in the database and for determining whether a given image was taken by a camera whose fingerprint is in the database.

Integrated fingerprint sensor and navigation device

Abstract: An apparatus is disclosed in a first embodiment of the invention as including a non-conductive substrate providing a first surface onto which a user can apply a fingerprint. A fingerprint sensing circuit is applied to a second surface of the non-conductive substrate opposite the first surface. The fingerprint sensing circuit is capable of sensing a fingerprint through the non-conductive substrate. A navigation device is positioned adjacent to (e.g., below) the non-conductive substrate and is capable of being manipulated by the user through the non-conductive substrate.

On latent fingerprint enhancement

Abstract: Automatic feature extraction in latent fingerprints is a challenging problem due to poor quality of most latents, such as unclear ridge structures, overlapped lines and letters, and overlapped fingerprints. We proposed a latent fingerprint enhancement algorithm which requires manually marked region of interest (ROI) and singular points. The core of the proposed enhancement algorithm is a novel orientation field estimation algorithm, which fits orientation field model to coarse orientation field estimated from skeleton outputted by a commercial fingerprint SDK. Experimental results on NIST SD27 latent fingerprint database indicate that by incorporating the proposed enhancement algorithm, the matching accuracy of the commercial matcher was significantly improved.

Integrated Fingerprint Sensor and Display

Abstract: A fingerprint swipe sensor includes fingerprint sensor lines disposed on a surface of an LCD protective glass covered on an opposite surface with motion sensing lines. The fingerprint swipe sensor also includes a controller coupled to the fingerprint sensor lines to capture a fingerprint image when a user's finger is swiped about the fingerprint sensor lines.

Improving Intra-Cellular Security Using Air Monitoring with RF Fingerprints

Abstract: Improved intra-cellular security is addressed using device-specific RF fingerprints to mitigate malicious network activity that can occur through unauthorized use of digital identities. In air monitoring applications where physical equipment constraints are not overly restrictive, RF fingerprinting remains a viable option for providing regional intra-cellular security for systems such as cellular telephone and last mile WiMax networks. Proof-of-concept results are provided for GSM signals given they are readily available in most areas. Recent RF fingerprinting work has demonstrated average device classification accuracies (serial number identification) of 92% using OFDM-based 802.11a preamble responses at SNR = 6 dB. The goal here was to determine if similar performance could be achieved using RF fingerprints extracted from near-transient and midamble regions of GSM signals. This was done using instantaneous phase responses from each region to form RF statistical fingerprints that are subsequently classified using Fisher-based MDA/ML processing. Considering all GSM device permutations from four different manufacturers, near-transient RF fingerprinting provided nearly 13% improvement in classification performance when compared with midamble RF fingerprinting and achieved average classification performance consistent with the 802.11a benchmark of 92% correct classification at SNR = 6 dB.

Biometric Mapping of Fingertip Eccrine Glands With Optical Coherence Tomography

Abstract: Biometric access control systems often employ fingerprint recognition based on the analysis of ridge patterns and minutiae. The inclusion of finer details, such as sweat pores, increases the accuracy of fingerprint identification. However, the distribution of sweat pores is difficult to extract from conventional fingerprint images, where image quality is susceptible to variations in fingertip surface conditions. Furthermore, a fingertip surface can be routinely counterfeited with a variety of techniques. We propose a more reliable biometric technology using spectral domain optical coherence tomography (SD-OCT) to image the subsurface of a fingertip. Experiments demonstrate high repeatability in clearly visualizing the distribution of sweat (eccrine) glands in live fingertips. Experiments on artificial fingertips confirm this is a spoof-proof approach. We believe these encouraging results demonstrate the value of SD-OCT as a robust fingerprint identification technology for biometric recognition.

Mosaicing Touchless and Mirror-Reflected Fingerprint Images

Abstract: Touchless fingerprint sensing technologies have been explored to solve problems in touch-based sensing techniques because they do not require any contact between a sensor and a finger. While they can solve problems caused by the contact of a finger, other difficulties emerge such as a view difference problem and a limited usable area due to perspective distortion. In order to overcome these difficulties, we propose a new touchless fingerprint sensing device capturing three different views at one time and a method for mosaicing these view-different images. The device is composed of a single camera and two planar mirrors reflecting side views of a finger, and it is an alternative to expensive multiple-camera-based systems. The mosaic method can composite the multiple view images by using the thin plate spline model to expand the usable area of a fingerprint image. In particular, to reduce the affect of perspective distortion, we select the regions in each view by minimizing the ridge interval variations in a final mosaiced image. Results are promising as our experiments show that mosaiced images offer 29% more true minutiae and 28% larger good quality area than one-view, unmosaiced images. Also, when the side-view images are matched to the mosaiced images, it gives more matched minutiae than matching with one-view frontal images. We expect that the proposed method can reduce the view difference problem and increase the usable area of a touchless fingerprint image. Furthermore, the proposed method can be applied to other biometric applications requiring a large template for recognition.

Sensor noise camera identification: countering counter-forensics

Abstract: In camera identification using sensor noise, the camera that took a given image can be determined with high certainty by establishing the presence of the camera's sensor fingerprint in the image. In this paper, we develop methods to reveal counter-forensic activities in which an attacker estimates the camera fingerprint from a set of images and pastes it onto an image from a different camera with the intent to introduce a false alarm and, in doing so, frame an innocent victim. We start by classifying different scenarios based on the sophistication of the attacker's activity and the means available to her and to the victim, who wishes to defend herself. The key observation is that at least some of the images that were used by the attacker to estimate the fake fingerprint will likely be available to the victim as well. We describe the socalled "triangle test" that helps the victim reveal attacker's malicious activity with high certainty under a wide range of conditions. This test is then extended to the case when none of the images that the attacker used to create the fake fingerprint are available to the victim but the victim has at least two forged images to analyze. We demonstrate the test's performance experimentally and investigate its limitations. The conclusion that can be made from this study is that planting a sensor fingerprint in an image without leaving a trace is significantly more difficult than previously thought.

Detecting Altered Fingerprints

Abstract: The widespread deployment of Automated Fingerprint Identification Systems (AFIS) in law enforcement and border control applications has prompted some individuals with criminal background to evade identification by purposely altering their fingerprints. Available fingerprint quality assessment software cannot detect most of the altered fingerprints since the implicit image quality does not always degrade due to alteration. In this paper, we classify the alterations observed in an operational database into three categories and propose an algorithm to detect altered fingerprints. Experiments were conducted on both real-world altered fingerprints and synthetically generated altered fingerprints. At a false alarm rate of 7%, the proposed algorithm detected 92% of the altered fingerprints, while a well-known fingerprint quality software, NFIQ, only detected 20% of the altered fingerprints.

Method and apparatus to combine biometric sensing and other functionality

Abstract: A multispectral system is disclosed that can image a biometric features as well as secondary objects or environments. In some embodiments machine readable information and a biometric images can be imaged using a multispectral systems disclosed herein. Such systems can be used to implement a number of processes that can include secondary authentication, alternate authentication, two-factor authentication, one-time authentication, etc. Some embodiments of the invention provide for greater functionality in a fingerprint reader in order to variously increase security, increase user convenience, decrease system size, decrease system complexity, decrease system cost, increase system throughput or transaction speed, provide alternative authentication, record and/or confirm the identity of a person.

Fit-sphere unwrapping and performance analysis of 3D fingerprints

Abstract: To solve problems associated with conventional 2D fingerprint acquisition processes including skin deformations and print smearing, we developed a noncontact 3D fingerprint scanner employing structured light illumination that, in order to be backwards compatible with existing 2D fingerprint recognition systems, requires a method of unwrapping the 3D scans into 2D equivalent prints. For the latter purpose of virtually flattening a 3D print, this paper introduces a fit-sphere unwrapping algorithm. Taking advantage of detailed 3D information, the proposed method defuses the unwrapping distortion by controlling the distances between neighboring points. Experimental results will demonstrate the high quality and recognition performance of the 3D unwrapped prints versus traditionally collected 2D prints. Furthermore, by classifying the 3D database into high- and low-quality data sets, we demonstrate that the relationship between quality and recognition performance holding for conventional 2D prints is achieved for 3D unwrapped fingerprints.

MCC: A baseline algorithm for fingerprint verification in FVC-onGoing

Abstract: This paper describes an improved version of the MCC fingerprint matching approach. An in-depth error analysis allowed us to point out the weakest points of the original MCC and to design: i) a more effective minutiae pair selection and ii) a more distortion-tolerant relaxation. The parameters of the new version have been tuned over a new larger dataset and the final algorithm has been evaluated on FVC-onGoing. The results show that MCC compares favorably with some of the most accurate commercial algorithms published in FVC-onGoing.

Illuminated Fingerprint Sensor and Method

Abstract: A fingerprint sensing device includes a fingerprint sensor and a light source proximate the fingerprint sensor. The light source is capable of providing multiple illumination formats. Each of the multiple illumination formats is associated with an operating status of the fingerprint sensor. The light source is positioned to emit light through the fingerprint sensor.

Database updating through user feedback in fingerprint-based Wi-Fi location systems

Abstract: Wi-Fi fingerprinting is a technique which can provide location in GPS-denied environments, relying exclusively on Wi-Fi signals. It first requires the construction of a database of “fingerprints”, i.e. signal strengths from different access points (APs) at different reference points in the desired coverage area. The location of the device is then obtained by measuring the signal strengths at its location, and comparing it with the different reference fingerprints in the database. The main disadvantage of this technique is the labour required to build and maintain the fingerprints database, which has to be rebuilt every time a significant change in the wireless environment occurs, such as installation or removal of new APs, changes in the layout of a building, etc. This paper investigates a new method to utilise user feedback as a way of monitoring changes in the wireless environment. It is based on a system of “points” given to each AP in the database. When an AP is switched off, the number of points associated with that AP will gradually reduce as the users give feedback, until it is eventually deleted from the database. If a new AP is installed, the system will detect it and update the database with new fingerprints. Our proposed system has two main advantages. First it can be used as a tool to monitor the wireless environment in a given place, detecting faulty APs or unauthorised installation of new ones. Second, it regulates the size of the database, unlike other systems where feedback is only used to insert new fingerprints in the database.