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Example of application of each transformation. (a) Original image. (b) Image cropped to simulate the minimum acquisition area for R (PIV IQS). (c) Image resampled to simulate the maximum allowed resolution for R (the 250-pixel segment highlighted in the original image here is 262 pixels). (d) Maximum barrel distortion allowed byR (the 250-pixel segment highlighted in the original image is here 272 pixels). (e) Image obtained by applying the Butterworth-like filter to simulate the minimum MTF values for R . (f) Noise added to simulate the minimum SNR for R . (g) Number of gray levels reduced to the minimum number required by R
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This paper addresses the problem of evaluating the ldquooperational qualityrdquo of fingerprint scanners, that is, the ability of acquiring images that maximize the accuracy of automated fingerprint recognition. The quality parameters commonly used to quantify the fidelity of a scanner in sensing the input pattern have been analyzed and a large exp...
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Biometric matching involves finding similarity between fingerprint images.The accuracy and speed of the matching algorithmdetermines its effectives. This researchaims at comparing two types of matching algorithms namely(a) matching using global orientation features and (b) matching using minutia
triangulation.The comparison is done using accuracy,...
Based on analyzing and experimenting a large number of the existing fingerprint image preprocessing algorithm, this paper presents a novel high-quality fingerprint image preprocessing algorithm. Taking full account of the inherent characteristics of the fingerprint image, the algorithm arranges overall features and local detail. The experiments sho...
Establishing correspondences between two minutia sets is a fundamental issue in fingerprint recognition. This paper proposes a new tensor matching strategy. First, the concept of minutia tensor matrix (simplified as MTM) is proposed. It describes the first-order features and second-order features of a matching pair. In the MTM, the diagonal element...
This paper presents an efficient Face and Fingerprint recognition algorithm combining ridge based matching for the latter and Eigen Face approach for the former. We assume we recognize the Face first and then the fingerprint recognition in sequence. A fast fingerprint authentication method is proposed, based on the core and minutiae detection of th...
Fingerprint recognition is a widely used biometric identificationmechanism. In case of correlation based fingerprint recognitiondetection of a consistent registration point is a crucial issue; thispoint can be a core point of a fingerprint. Many techniques havebeen proposed but success rate is highly dependent on input usedand accurate core point d...
Citations
... Unfortunately, current unlocking mechanisms often cannot fully meet these requirements. To illustrate the mismatches between functionalities and requirements, we consider three main categories of unlocking schemes: i) mechanical key or electronic card [1], [2], ii) keyless access via passwords or drawing patterns [3], [4], and iii) biometrics-based identity verification [5], [6]. ...
Door lock is regarded as a critical line of defending the privacy and security of personal areas. However, for inner doors in environments like factories, existing locking mechanisms can be poor in user-friendliness and high in cost. For instance, mechanical locks require carrying keys that inevitably compromise user experiences, while smart locks always require non-trivial sensors. Therefore, inner doors urgently require a lightweight unlocking scheme that can properly balance user-friendliness, cost, and security. To this end, we propose HandKey as a keyless unlocking scheme to supplement existing lock systems. HandKey relies on two principles: the simplicity of hand knocking doors and the uniqueness of vibration triggered by the knocking force. In other words, a door and a hand knocking it jointly form a unique physical system that generates hand-dependent and user-specific vibration signatures uniquely representing a user identity. In designing HandKey, we first analyze the vibration mechanism behind it and the impacts of gestures and door materials on vibration signatures. Then we innovatively construct a signal processing and deep learning-based pipeline to extract signatures robust to variable knocking behaviors for representing user identity. Finally, we implement a HandKey prototype and use extensive evaluation to demonstrate its security and effectiveness.
... The increase of accuracy is treated in many papers [12,[26][27][28]. Licensed software are much more accurate than the free ones, whose results are comparable with the ones obtained manually by an expert [29,30]. ...
Biometric devices identify persons based on the minutiae extracted from fingerprint images. Image quality is very important in this process. Usually, fingerprint images have low quality and in many cases they are obtained in various positions. The paper focuses on increasing minutiae detected number by fusing two fingerprint images obtained in various positions. Biorthogonal wavelets have advantages compared to orthogonal wavelets. Fusion is performed in wavelet domain by implementing biorthogonal wavelet. Terminations and bifurcations are extracted from the original and fused images using licensed software Papillon 9.02 and manually extraction by an expert. Biorthogonal Wavelet transform is implemented in the image fusion process, yielding in the increased number of the minutiae compared to the original one. Different biorthogonal wavelets are experimented and various results are obtained. Finding the appropriate wavelet is important in the fusion process since it has a direct impact in the number of minutiae extracted. Based on the number of minutiae and MSE results, the appropriate wavelet to be used in the fusion process is defined.
... These studies did utilize the 3D targets for some white-box testing, but were primarily focused on evaluations related to end-to-end matching performance. This is also the case with [14], where the authors investigate the effect of relaxing each metric outlined in the PIV-071006 in terms of black-box matching accuracy on a database of real fingerprints. ...
Typical evaluations of fingerprint recognition systems consist of end-to-end black-box evaluations, which assess performance in terms of overall identification or authentication accuracy. However, these black-box tests of system performance do not reveal insights into the performance of the individual modules, including image acquisition, feature extraction, and matching. On the other hand, white-box evaluations, the topic of this paper, measure the individual performance of each constituent module in isolation. While a few studies have conducted white-box evaluations of the fingerprint reader, feature extractor, and matching components, no existing study has provided a full system, white-box analysis of the uncertainty introduced at each stage of a fingerprint recognition system. In this work, we extend previous white-box evaluations of fingerprint recognition system components and provide a unified, in-depth analysis of fingerprint recognition system performance based on the aggregated white-box evaluation results. In particular, we analyze the uncertainty introduced at each stage of the fingerprint recognition system due to adverse capture conditions (i.e., varying illumination, moisture, and pressure) at the time of acquisition. Our experiments show that a system that performs better overall, in terms of black-box recognition performance, does not necessarily perform best at each module in the fingerprint recognition system pipeline, which can only be seen with white-box analysis of each sub-module. Findings such as these enable researchers to better focus their efforts in improving fingerprint recognition systems.
... Hence vendors are required to demonstrate that their sensors can acquire a high-fidelity image with low-noise characteristics. Existing studies have evaluated the performance of sensors in terms of their resilience to external environmental factors (temperature and humidity), intrinsic subject-dependent factors (skin humidity and pressure) [3], operational quality [4], their interoperability [5], and finger liveness detection [6]. Arora This research was supported by grant no. ...
... *At the time this research was conducted, Sunpreet was affiliated with the Dept. of Computer Science and Engineering, Michigan State University. 4 Fidelity refers to the degree of exactness with which friction ridge patterns on a finger are reproduced by the sensor et. al [7] have designed and fabricated 3D fingerprint targets and whole hand targets for repeatable evaluation and calibration of fingerprint sensors. ...
... Un bloc de l'image bien défini possède une direction locale constante. -Sur un bloc, les niveaux de gris des crêtes et des vallées constituent une forme sinusoïdale le long de la direction normale à l'orientation locale des crêtes (voir la figure 1.6 [CFM08], la qualité du capteur dépend de plusieurs facteurs comme : la surface d'acquisition, la résolution (aujourd'hui autour de 500 ppi équivalente à 19.69 pixels par millimètre), la quantification des niveaux de gris (256 niveaux par exemple) ou la précision géométrique. Etudier la corrélation entre la qualité du capteur et les performances de reconnaissance est un point important qui permet de définir les exigences minimales des capteurs utilisés dans les applications biométriques. ...
En référence à la sécurité informatique, la biométrie concerne l’utilisation des caractéristiques morphologiques ou comportementales pour déterminer ou vérifier l’identité d’un utilisateur.Récemment, des discussions sur la sécurité des systèmes biométriques ont émergé. Le stockage des données de référence pose de sérieux problèmes de sécurité et d’invasion de vie privée : manipulation d’informations sensibles, reconstruction de la biométrie d’origine à partir du modèle stocké, construction d’un échantillon biométrique falsifié, utilisation secondaire des informations biométriques (surveillance, discrimination, etc.) ou l’impossibilité de révoquer l’identifiant biométrique lorsqu’un vol d’identité à eu lieu.La sécurité du modèle biométrique est l’une des tâches les plus cruciales dans la conception d’un système biométrique sécurisé. Considérant la modalité d’empreintes digitales, nous proposons dans cette thèse deux types de solution à ce problème. La première au niveau algorithmique et la seconde au niveau architectural.Dans l’approche fonctionnelle ou algorithmique, nous traitons des schémas de protection des modèles biométriques. Il s’agit d’un nouveau concept dont le but est de générer une biométrie révocable en appliquant des transformations, idéalement à sens unique. Plusieurs schémas de biométrie révocable ont été proposés dans la littérature, mais pour l’heure, des efforts sont attendus pour améliorer leur fiabilité. Un schéma de biométrie révocable est une chaine de traitement qui inclut les phases d’extraction des caractéristiques, de transformation et de comparaison. Toutes ces phases sont traitées dans cette thèse. Principalement, nous nous intéressons aux descripteurs de texture d’empreintes digitales. Un premier schéma révocable, en utilisant une description de la texture globale de l’empreinteest proposé. Pour améliorer les résultats, ce schéma est étendu aux minuties. Une approche de transformation par projection aléatoire est ensuite opérée.L’une des diffcultés est d’évaluer correctement le schéma de biométrie révocable généré. Nous proposons un modèle d’évaluation basé sur un ensemble de métriques quantitatives, pour mesurer les critères de sécurité et de protection de vie privée souhaités.Dans la seconde solution, nous proposons d’utiliser une architecture fermée pour le système de vérification biométrique. Les cartes à puce sont utilisées pour une meilleure gestion des données d’authentification de l’utilisateur. Un système de biométrie révocable avec un algorithme de comparaison sur la carte est proposé. Un tel système offre des avantages combinés de révocabilité et de confidentialité du modèle biométrique. Nous utilisons une JavaCard que nous gérons conformément à la norme PKCS15 pour plus d’interopérabilité.Nous proposons ensuite d’étudier les possibilités de menaces de vie privée dans l’application des passeports biométriques. Nous concluons par le fait que la biométrie révocable serait souhaitable pour améliorer la protection des données biométriques contenues dans la puce du passeport.
... It can also be observed that the insignificant features of truncated fingerprints may easily disappear after performing image reconstruction and enhancement procedures. Nevertheless, existing detection algorithms [10,11] for fingerprint image analysis always focused on checking the adequate feature number of minutiae/ridges [12,13] or image qualities [14][15][16], and most of algorithms spend a lot of time on determining the validity of a fingerprint [17][18][19]. For example, one of the most reliable fingerprint quality inspection systems is the Fingerprint Image Quality (NFIQ) [20] which was developed and maintained by National Institute of Standard and Technology (NIST) in United States. ...
A sweeping fingerprint sensor converts fingerprints on a row by row basis through image reconstruction techniques. However, a built fingerprint image might appear to be truncated and distorted when the finger was swept across a fingerprint sensor at a non-linear speed. If the truncated fingerprint images were enrolled as reference targets and collected by any automated fingerprint identification system (AFIS), successful prediction rates for fingerprint matching applications would be decreased significantly. In this paper, a novel and effective methodology with low time computational complexity was developed for detecting truncated fingerprints in a real time manner. Several filtering rules were implemented to validate existences of truncated fingerprints. In addition, a machine learning method of supported vector machine (SVM), based on the principle of structural risk minimization, was applied to reject pseudo truncated fingerprints containing similar characteristics of truncated ones. The experimental result has shown that an accuracy rate of 90.7% was achieved by successfully identifying truncated fingerprint images from testing images before AFIS enrollment procedures. The proposed effective and efficient methodology can be extensively applied to all existing fingerprint matching systems as a preliminary quality control prior to construction of fingerprint templates.
... When these three parameters were degraded simultaneously, the drop in performance was larger than the sum of the individual performance drops. (373) Saijo et al. propose ultrasound imaging of fingerprints for medical purposes. The proposed method allows obtaining clear 3D images of the finger surface, but also of the rear surface of the fingerprint (dermal papillae), in vivo (374). ...
The purpose of this paper is to review the scientific literature from August 2007 to July 2010. The review is focused on more than 420 published papers. The review will not cover information coming from international meetings available only in abstract form.
... On the other hand, the situation is different in totally-automated biometric systems, where: i) the images are stored but used only for automated comparisons, or ii) only fingerprint templates are stored. As discussed in a recent work [1], in these cases it may be more appropriate to define the fingerprint scanner quality as the ability of a fingerprint scanner to acquire images that maximize the accuracy of automated recog- nition algorithms (operational quality). A first advantage of the operational quality is that it allows to estimate the loss of performance of a scanner compliant to a given IQS with respect to an "ideal scanner". ...
... A first advantage of the operational quality is that it allows to estimate the loss of performance of a scanner compliant to a given IQS with respect to an "ideal scanner". In [1], the impact on the recognition accuracy of each quality parameter has been separately assessed, to understand which are the most critical requirements. This work evaluates the simultaneous effect of all the requirements referring to two recently released IQS for single-finger scanners (PIV and PassDEÜV) and proposes three new sets of IQS (CNIPA-A, CNIPA-B and CNIPA-C) targeted to different applications where single finger scanners are required. ...
... In order to evaluate the impact on fingerprint recognition accuracy of the IQS de- scribed in section 2, a systematic experimentation has been carried out. Following the testing methodology introduced in [1] and using the same test database, fingerprint images acquired by hypothetical scanners compliant with each IQS have been simu- lated. To this purpose, the transformations described in [1] have been sequentially applied to the original fingerprint images according to the worst-case scenario hy- pothesized in Table 2. ...
This paper analyzes two recently released image quality specifications for single-finger scanners and proposes three new specifications targeted to different types of applications. A comparison of the potential effects on fingerprint recognition accuracy of the various specifications is carried out using an approach based on the definition of “operational quality”. The experimental results show that the three new image quality specifications proposed in this work have an accuracy/cost tradeoff better than the existing ones.
