Proceedings Article•
Video-based fingerphoto recognition with anti-spoofing techniques with smartphone cameras
03 Oct 2013-pp 1-12
TL;DR: A novel approach to capture multiple fingerphotos in a videostream with a smartphone camera and the processing of the photos for the finger recognition is discussed in this paper, which offers a convenient and efficient way to capturemultiple samples of a biometric instance in a short time frame.
Abstract: This work is concerned with the acquisition of fingerprints samples on smartphones with the built-in smartphone camera. A novel approach to capture multiple fingerphotos in a videostream with a smartphone camera and the processing of the photos for the finger recognition is discussed in this paper. The proposed technique offers a convenient and efficient way to capture multiple samples of a biometric instance in a short time frame. Due the fact that fingerphotos can be easily replicated with low effort (e.g. print outs with an ordinary printer) and thus are vulnerable to presentation attacks, anti-spoofing algorithms were developed to detect such spoof attempts. The algorithms for the detection and segmentation of the finger as well the preprocessing of the photo with graphical operations and anti-spoofing were implemented in a prototype as application for the Android operating system. User tests are performed to evaluate the usability and to create a database of biometric samples for offline evaluation of the recognition performance. Further tests are done with diverse artefacts such as printed finger images, fake fingers of gelatin, gummy and silicon as well finger replay videos to measure the resistance of the developed solution against presentation attacks.
Citations
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17 Dec 2015
TL;DR: A novel ScatNet feature based fingerphoto matching approach is proposed to aid the matching process and to attenuate the effect of capture variations, and results show improved performance across multiple challenges present in the database.
Abstract: Authenticating fingerphoto images captured using a smartphone camera, provide a good alternate solution in place of traditional pin or pattern based approaches. There are multiple challenges associated with fingerphoto authentication such as background variations, environmental illumination, estimating finger position, and camera resolution. In this research, we propose a novel ScatNet feature based fingerphoto matching approach. Effective fingerphoto segmentation and enhancement are performed to aid the matching process and to attenuate the effect of capture variations. Further, we propose and create a publicly available smartphone fingerphoto database having three different subsets addressing the challenges of environmental illumination and background, along with their corresponding live scan fingerprints. Experimental results show improved performance across multiple challenges present in the database.
53 citations
Cites background or methods from "Video-based fingerphoto recognition..."
...However, it is not captured using smart-phone cameras and has minimal variations in terms of illumination and background. ground, we observe that the skin color of the finger is uniform and serves as a distinguishing feature....
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...Following this observation, we propose the adaptive skin color thresholding for fingerphoto segmentation....
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Proceedings Article•
01 Sep 2014
TL;DR: A standalone modular biometric system based on periocular information to authenticate towards device and the best performance achieved with GMR = 89.38% at FMR = 0.01% indicates the applicability of the proposed peroicular based mobile authentication system in a real-life scenario.
Abstract: The increasing usage of smartphones has raised security concerns regarding these devices due to presence of high amount of personal and sensitive data. The risk is higher without a proper mechanism to handle the authentication to access the smartphone device. In this work, we present a standalone modular biometric system based on periocular information to authenticate towards device. The proposed system has been implemented on the Android operating system. We field tested and evaluated the proposed system using a new database acquired capturing samples with three different devices. We apply the three well known feature extraction techniques, SIFT, SURF and BSIF independently in the proposed peroicular based authentication system. The best performance achieved with GMR = 89.38% at FMR = 0.01% indicates the applicability of the proposed periocular based mobile authentication system in a real-life scenario.
41 citations
Cites background or methods from "Video-based fingerphoto recognition..."
...Motivated by works on fingerprint recognition [6], [7], in this work, we explore the periocular information for contactless authentication on smartphones....
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...Robust approaches have been proposed to use the camera as contactless fingerprint sensor for authentication [6], [7], [8]....
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TL;DR: In this article, the state-of-the-art in the field of touchless 2D fingerprint recognition at each stage of the recognition process is summarized and technical considerations and trade-offs of the presented methods along with open issues and challenges.
Abstract: Touchless fingerprint recognition represents a rapidly growing field of research which has been studied for more than a decade Through a touchless acquisition process, many issues of touch-based systems are circumvented, eg, the presence of latent fingerprints or distortions caused by pressing fingers on a sensor surface However, touchless fingerprint recognition systems reveal new challenges In particular, a reliable detection and focusing of a presented finger as well as an appropriate preprocessing of the acquired finger image represent the most crucial tasks Also, further issues, eg, interoperability between touchless and touch-based fingerprints or presentation attack detection, are currently investigated by different research groups Many works have been proposed so far to put touchless fingerprint recognition into practice Published approaches range from self identification scenarios with commodity devices, eg, smartphones, to high performance on-the-move deployments paving the way for new fingerprint recognition application scenariosThis work summarizes the state-of-the-art in the field of touchless 2D fingerprint recognition at each stage of the recognition process Additionally, technical considerations and trade-offs of the presented methods are discussed along with open issues and challenges An overview of available research resources completes the work
27 citations
03 Jun 2020
TL;DR: An algorithm which comprises segmentation, enhancement, Deep Scattering Network based feature extraction, and Random Decision Forest to authenticate finger-selfies is proposed and results and comparison with existing algorithms show the efficacy of the proposed algorithm.
Abstract: With the advancements in technology, smartphones’ capabilities have increased immensely. For instance, the smartphone cameras are being used for face and ocular biometric-based authentication. This research proposes finger-selfie based authentication mechanism, which uses a smartphone camera to acquire a selfie of a finger. In addition to personal device-level authentication, finger-selfies may also be matched with livescan fingerprints present in the legacy/national ID databases for remote or touchless authentication. We propose an algorithm which comprises segmentation, enhancement, Deep Scattering Network based feature extraction, and Random Decision Forest to authenticate finger-selfies. This paper also presents one of the largest finger-selfie database with over 19, 400 images. The images in the IIIT-D Smartphone Finger-selfie Database v2 are captured using multiple smartphones and include variations due to background, illumination, resolution, and sensors. Results and comparison with existing algorithms show the efficacy of the proposed algorithm which yields equal error rates in the range of 2.1 – 5.2% for different experimental protocols.
23 citations
01 Jan 2017
TL;DR: A novel end-to-end finger photo matching pipeline is proposed by studying the effect of different environmental conditions in fingerphoto matching by creating a publicly available fingerphoto dataset, IIITD SmartPhone Fingerphoto Database v1, and shows that the proposed matching pipeline provides an improved performance when compared with some of the existing approaches.
Abstract: With a rapid growth in smartphone technology, there is a need to provide secured access to critical data using personal authentication. Existing access mechanisms such as pin and password suffer due to lack of security from shoulder-surfing attacks. Use of biometric modalities such as fingerprint are currently explored in existing smartphones as a more secure authentication mechanism. Typically, fingerprint capturing requires an extra sensor, adding to the cost of the device as well as denying backend services to existing smartphone devices. Using a rear camera captured fingerphoto image provides a cheap alternate option, without the need for a dedicated sensor for capturing images. However, unlike fingerprints fingerphoto images are captured in a more uncontrolled environment including any outdoor conditions. Hence, fingerphoto matching is prone to many challenges such as varying environmental illumination and surrounding background. We propose a novel end-to-end fingerphoto matching pipeline by studying the effect of different environmental conditions in fingerphoto matching. The pipeline consists of the following major contributions: (i) a segmentation technique to extract the fingerphoto region of interest from varying background, (ii) an enhancement module to neutralize the illumination imbalance and increase the ridge–valley contrast, (iii) a scattering network based fingerphoto representation technique to deal with the pose variations, whose resultant features are invariant to geometric transformations, and (iv) a learning based matching technique to accommodate maximum variations occurring in fingerphoto images. To experimentally study the challenging conditions such as background and illumination, we create a publicly available fingerphoto dataset, IIITD SmartPhone Fingerphoto Database v1, along with the corresponding live-scan prints. The experiments performed on the dataset shows that the proposed matching pipeline provides an improved performance when compared with some of the existing approaches.
20 citations
References
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01 Jul 2007
TL;DR: A novel method for Fingerprint recognition is considered using a combination of Fast Fourier Transform and Gabor Filters to enhancement the fingerprint image was captured using a UareU 4000 fingerprint reader of Digital Person, Inc.
Abstract: Fingerprint recognition is one of the most popular and successful methods used for person identification, which takes advantage of the fact that the fingerprint has some unique characteristics called minutiae; which are points where a curve track finishes, intersect with other track or branches off. Biometric identification systems using fingerprints patterns are called AFIS (Automatic Fingerprint Identification System). In this paper a novel method for Fingerprint recognition is considered using a combination of Fast Fourier Transform (FFT) and Gabor Filters to enhancement the fingerprint image was captured using a UareU 4000 fingerprint reader of Digital Person, Inc.
125 citations
17 May 2011
TL;DR: A first step towards a novel biometric authentication approach applying cell phone cameras capturing fingerprint images as biometric traits is proposed and shows a biometric performance with an Equal Error Rate of 4.5% by applying a commercial extractor/comparator and without any preproccesing on the images.
Abstract: Mobile phones with a camera function are capable of capturing image and processing tasks. Fingerprint recognition has been used in many different applications where high security is required. A first step towards a novel biometric authentication approach applying cell phone cameras capturing fingerprint images as biometric traits is proposed. The proposed method is evaluated using 1320 fingerprint images from each embedded capturing device. Fingerprints are collected by a Nokia N95 and a HTC Desire. The overall results of this approach show a biometric performance with an Equal Error Rate (EER) of 4.5% by applying a commercial extractor/comparator and without any preproccesing on the images.
83 citations
Proceedings Article•
27 Sep 2012TL;DR: The proposed authentication method is analyzed for feasibility and implemented in a prototype as application for the Android operating system, and a biometric database containing photos of the two test devices from 41 test subjects is created.
Abstract: This paper is concerned with the authentication of people on smartphones using fingerphoto recognition. In this work, fingerphotos are captured with the built-in camera of the smartphone. The proposed authentication method is analyzed for feasibility and implemented in a prototype as application for the Android operating system. Algorithms for the capture process are developed to ensure a minimum of quality of the captured photos to enable a reliable fingerphoto recognition. Several methods for preprocessing of the captured samples are analyzed and performant solutions to evaluate the photos are developed to enhance the recognition rates. This is achieved by evaluating a wide range of different parameters and configurations of the algorithms as well as various combinations of preprocessing chains for the captured samples. The operations for preprocessing are selected with respect to their computational effort to guarantee that they can be executed on a smartphone with limited computation and memory capacity. The developed prototype is evaluated in user tests with two different smartphones. Additionally, a biometric database containing photos of the two test devices from 41 test subjects is created. These fingerphotos are used to evaluate and optimize the procedures.
67 citations
01 Feb 2008
TL;DR: A new focus-measurement algorithm using the secondary partial derivatives and a quality estimation utilizing the coherence and symmetry of gradient distribution is proposed for fingerprint-verification systems that use a camera embedded in a mobile device.
Abstract: This paper proposes a recognizable-image selection algorithm for fingerprint-verification systems that use a camera embedded in a mobile device. A recognizable image is defined as the fingerprint image which includes the characteristics that are sufficiently discriminating an individual from other people. While general camera systems obtain focused images by using various gradient measures to estimate high-frequency components, mobile cameras cannot acquire recognizable images in the same way because the obtained images may not be adequate for fingerprint recognition, even if they are properly focused. A recognizable image has to meet the following two conditions: First, valid region in the recognizable image should be large enough compared with other nonrecognizable images. Here, a valid region is a well-focused part, and ridges in the region are clearly distinguishable from valleys. In order to select valid regions, this paper proposes a new focus-measurement algorithm using the secondary partial derivatives and a quality estimation utilizing the coherence and symmetry of gradient distribution. Second, rolling and pitching degrees of a finger measured from the camera plane should be within some limit for a recognizable image. The position of a core point and the contour of a finger are used to estimate the degrees of rolling and pitching. Experimental results show that our proposed method selects valid regions and estimates the degrees of rolling and pitching properly. In addition, fingerprint-verification performance is improved by detecting the recognizable images.
45 citations
Proceedings Article•
01 Jan 2010TL;DR: The purpose of the system is to provide an infrastructure which allows the implementation and usage of alternative authentication procedures and could lead to an increased acceptance of authentication on smartphones and thus an increased security of the devices.
Abstract: In this paper we present the design of a modular authentication system, which enables users to select an authentication procedure by preference. A survey, carried out by N.L. Clarke and S.M. Furnell [CF05], proved the classical PIN-authentication to be inconvenient for many users. Passwords and PINs are either secure or easy to remember. Since humans tend to forget complex permutations of characters and numbers, the chosen secrets are often insecure. The purpose of the system is to provide an infrastructure which allows the implementation and usage of alternative authentication procedures. This approach could lead to an increased acceptance of authentication on smartphones and thus an increased security of the devices. A prototype based on the concepts presented in this paper was implemented for the android operating system and a gait recognition module is being actively developed. Further modules like face recognition, voice recognition or graphical authentication schemes can be integrated which depicts the flexibility of the system.
8 citations