| 1. |
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| 2. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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A Review Of Schemes For Fingerprint Image Quality Computation
- 2005
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Ingår i: COST Action 275. - Luxembourg : EU Publications Office (OPOCE). - 9789289800198 ; , s. 3-6
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Konferensbidrag (refereegranskat)abstract
- Fingerprint image quality affects heavily the performance of fingerprint recognition systems. This paper reviews existing approaches for fingerprint image quality computation. We also implement, test and compare a selection of them using the MCYT database including 9000 fingerprint images. Experimental results show that most of the algorithms behave similarly.
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| 3. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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A Survey of Super-Resolution in Iris Biometrics with Evaluation of Dictionary-Learning
- 2019
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Ingår i: IEEE Access. - Piscataway, NJ : IEEE. - 2169-3536. ; 7, s. 6519-6544
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Tidskriftsartikel (refereegranskat)abstract
- The lack of resolution has a negative impact on the performance of image-based biometrics. While many generic super-resolution methods have been proposed to restore low-resolution images, they usually aim to enhance their visual appearance. However, an overall visual enhancement of biometric images does not necessarily correlate with a better recognition performance. Reconstruction approaches need thus to incorporate specific information from the target biometric modality to effectively improve recognition performance. This paper presents a comprehensive survey of iris super-resolution approaches proposed in the literature. We have also adapted an Eigen-patches reconstruction method based on PCA Eigentransformation of local image patches. The structure of the iris is exploited by building a patch-position dependent dictionary. In addition, image patches are restored separately, having their own reconstruction weights. This allows the solution to be locally optimized, helping to preserve local information. To evaluate the algorithm, we degraded high-resolution images from the CASIA Interval V3 database. Different restorations were considered, with 15 × 15 pixels being the smallest resolution evaluated. To the best of our knowledge, this is among the smallest resolutions employed in the literature. The experimental framework is complemented with six publicly available iris comparators, which were used to carry out biometric verification and identification experiments. Experimental results show that the proposed method significantly outperforms both bilinear and bicubic interpolation at very low-resolution. The performance of a number of comparators attain an impressive Equal Error Rate as low as 5%, and a Top-1 accuracy of 77-84% when considering iris images of only 15 × 15 pixels. These results clearly demonstrate the benefit of using trained super-resolution techniques to improve the quality of iris images prior to matching. © 2018, Emerald Publishing Limited.
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| 4. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Combining multiple matchers for fingerprint verification : A case study in biosecure network of excellence
- 2007
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Ingår i: Annales des télécommunications. - Paris, France : Springer. - 0003-4347 .- 1958-9395. ; 62:1-2, s. 62-82
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Tidskriftsartikel (refereegranskat)abstract
- We report on experiments for the fingerprint modality conducted during the First BioSecure Residential Workshop. Two reference systems for fingerprint verification have been tested together with two additional non-reference systems. These systems follow different approaches of fingerprint processing and are discussed in detail. Fusion experiments involving different combinations of the available systems are presented. The experimental results show that the best recognition strategy involves both minutiae-based and correlation-based measurements. Regarding the fusion experiments, the best relative improvement is obtained when fusing systems that are based on heterogeneous strategies for feature extraction and/or matching. The best combinations of two/three/four systems always include the best individual systems whereas the best verification performance is obtained when combining all the available systems.
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| 5. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Cross-sensor periocular biometrics in a global pandemic : Comparative benchmark and novel multialgorithmic approach
- 2022
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Ingår i: Information Fusion. - Amsterdam : Elsevier. - 1566-2535 .- 1872-6305. ; 83-84, s. 110-130
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Tidskriftsartikel (refereegranskat)abstract
- The massive availability of cameras and personal devices results in a wide variability between imaging conditions, producing large intra-class variations and a significant performance drop if images from heterogeneous environments are compared for person recognition purposes. However, as biometric solutions are extensively deployed, it will be common to replace acquisition hardware as it is damaged or newer designs appear or to exchange information between agencies or applications operating in different environments. Furthermore, variations in imaging spectral bands can also occur. For example, face images are typically acquired in the visible (VIS) spectrum, while iris images are usually captured in the near-infrared (NIR) spectrum. However, cross-spectrum comparison may be needed if, for example, a face image obtained from a surveillance camera needs to be compared against a legacy database of iris imagery. Here, we propose a multialgorithmic approach to cope with periocular images captured with different sensors. With face masks in the front line to fight against the COVID-19 pandemic, periocular recognition is regaining popularity since it is the only region of the face that remains visible. As a solution to the mentioned cross-sensor issues, we integrate different biometric comparators using a score fusion scheme based on linear logistic regression This approach is trained to improve the discriminating ability and, at the same time, to encourage that fused scores are represented by log-likelihood ratios. This allows easy interpretation of output scores and the use of Bayes thresholds for optimal decision-making since scores from different comparators are in the same probabilistic range. We evaluate our approach in the context of the 1st Cross-Spectral Iris/Periocular Competition, whose aim was to compare person recognition approaches when periocular data from visible and near-infrared images is matched. The proposed fusion approach achieves reductions in the error rates of up to 30%–40% in cross-spectral NIR–VIS comparisons with respect to the best individual system, leading to an EER of 0.2% and a FRR of just 0.47% at FAR = 0.01%. It also represents the best overall approach of the mentioned competition. Experiments are also reported with a database of VIS images from two different smartphones as well, achieving even bigger relative improvements and similar performance numbers. We also discuss the proposed approach from the point of view of template size and computation times, with the most computationally heavy comparator playing an important role in the results. Lastly, the proposed method is shown to outperform other popular fusion approaches in multibiometrics, such as the average of scores, Support Vector Machines, or Random Forest. © 2022 The Authors
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| 6. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Fingerprint Databases and Evaluation
- 2015. - 2
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Ingår i: Encyclopedia of Biometrics. - New York : Springer Science+Business Media B.V.. - 9781489974877 - 9781489974884 ; , s. 599-606
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Bokkapitel (refereegranskat)abstract
- This is an excerpt from the contentSynonymsFingerprint benchmark; Fingerprint corpora; Fingerprint datasetDefinitionFingerprint databases are structured collections of fingerprint data mainly used for either evaluation or operational recognition purposes.Fingerprint data in databases for evaluation are usually detached from the identity of corresponding individuals. These databases are publicly available for research purposes, and they usually consist of raw fingerprint images acquired with live-scan sensors or digitized from inked fingerprint impressions on paper. Databases for evaluation are the basis for research in automatic fingerprint recognition, and together with specific experimental protocols, they are the basis for a number of technology evaluations and benchmarks. This is the type of fingerprint databases further covered here.On the other hand, fingerprint databases for operational recognition are typically proprietary, they usually incorporate personal information about the enrolled people together with the fingerprint data, and they can incorporate either raw fingerprint image data or some form of distinctive fingerprint descriptors such as minutiae templates. These fingerprint databases represent one of the modules in operational automated fingerprint recognition systems, and they will not be adressed here.
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| 7. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Fingerprint Recognition
- 2009
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Ingår i: Guide to Biometric Reference Systems and Performance Evaluation. - London : Springer London. - 9781848002913 - 9781848002920 ; , s. 51-88
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- First, an overview of the state of the art in fingerprint recognition is presented, including current issues and challenges. Fingerprint databases and evaluation campaigns, are also summarized. This is followed by the description of the BioSecure Benchmarking Framework for Fingerprints, using the NIST Fingerpint Image Software (NFIS2), the publicly available MCYT-100 database, and two evaluation protocols. Two research systems are compared within the proposed framework. The evaluated systems follow different approaches for fingerprint processing and are discussed in detail. Fusion experiments involving different combinations of the presented systems are also given. The NFIS2 software is also used to obtain the fingerprint scores for the multimodal experiments conducted within the BioSecure Multimodal Evaluation Campaign(BMEC’2007) reported in Chap.11.
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| 8. |
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| 9. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Periocular Biometrics : A Modality for Unconstrained Scenarios
- 2024
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Ingår i: Computer. - Piscataway, NJ : IEEE Computer Society. - 0018-9162 .- 1558-0814. ; 57:6, s. 40-49
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Tidskriftsartikel (refereegranskat)abstract
- This article discusses the state of the art in periocular biometrics, presenting an overall framework encompassing the field's most significant research aspects, which include ocular definition, acquisition, and detection; identity recognition; and ocular soft-biometric analysis. © 1970-2012 IEEE.
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| 10. |
- Alonso-Fernandez, Fernando, et al.
(författare)
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Quality-Based Conditional Processing in Multi-Biometrics : Application to Sensor Interoperability
- 2010
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Ingår i: IEEE transactions on systems, man and cybernetics. Part A. Systems and humans. - Piscataway, NJ, USA : IEEE Press. - 1083-4427 .- 1558-2426. ; 40:6, s. 1168-1179
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Tidskriftsartikel (refereegranskat)abstract
- As biometric technology is increasingly deployed, it will be common to replace parts of operational systems with newer designs. The cost and inconvenience of reacquiring enrolled users when a new vendor solution is incorporated makes this approach difficult and many applications will require to deal with information from different sources regularly. These interoperability problems can dramatically affect the performance of biometric systems and thus, they need to be overcome. Here, we describe and evaluate the ATVS-UAM fusion approach submitted to the quality-based evaluation of the 2007 BioSecure Multimodal Evaluation Campaign, whose aim was to compare fusion algorithms when biometric signals were generated using several biometric devices in mismatched conditions. Quality measures from the raw biometric data are available to allow system adjustment to changing quality conditions due to device changes. This system adjustment is referred to as quality-based conditional processing. The proposed fusion approach is based on linear logistic regression, in which fused scores tend to be log-likelihood-ratios. This allows the easy and efficient combination of matching scores from different devices assuming low dependence among modalities. In our system, quality information is used to switch between different system modules depending on the data source (the sensor in our case) and to reject channels with low quality data during the fusion. We compare our fusion approach to a set of rule-based fusion schemes over normalized scores. Results show that the proposed approach outperforms all the rule-based fusion schemes. We also show that with the quality-based channel rejection scheme, an overall improvement of 25% in the equal error rate is obtained. © 2010 IEEE.
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| 11. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Quality Measures in Biometric Systems
- 2012
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Ingår i: IEEE Security and Privacy. - New York, NY : IEEE Computer Society. - 1540-7993 .- 1558-4046. ; 10:6, s. 52-62
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Tidskriftsartikel (refereegranskat)abstract
- Biometric technology has been increasingly deployed in the last decade, offering greater security and convenience than traditional methods of personal recognition. But although the performance of biometric systems is heavily affected by the quality of biometric signals, prior work on quality evaluation is limited. Quality assessment is a critical issue in the security arena, especially in challenging scenarios (e.g. surveillance cameras, forensics, portable devices or remote access through Internet). Different questions regarding the factors influencing biometric quality and how to overcome them, or the incorporation of quality measures in the context of biometric systems have to be analyzed first. In this paper, a review of the state-of-the-art in these matters is provided, giving an overall framework of the main factors related to the challenges associated with biometric quality.
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| 12. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Quality Measures in Biometric Systems
- 2015. - 2
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Ingår i: Encyclopedia of Biometrics. - New York : Springer Science+Business Media B.V.. - 9781489974877 - 9781489974884 ; , s. 1287-1297
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Bokkapitel (refereegranskat)abstract
- This is an excerpt from the contentSynonymsQuality assessment; Biometric quality; Quality-based processingDefinitionSince the establishment of biometrics as a specific research area in the late 1990s, the biometric community has focused its efforts in the development of accurate recognition algorithms [1]. Nowadays, biometric recognition is a mature technology that is used in many applications, offering greater security and convenience than traditional methods of personal recognition [2].During the past few years, biometric quality measurement has become an important concern after a number of studies and technology benchmarks that demonstrate how performance of biometric systems is heavily affected by the quality of biometric signals [3]. This operationally important step has been nevertheless under-researched compared to the primary feature extraction and pattern recognition tasks [4]. One of the main challenges facing biometric technologies is performance degradation in less controlled situations, and the problem of biometric quality measurement has arisen even stronger with the proliferation of portable handheld devices, with at-a-distance and on-the-move acquisition capabilities. These will require robust algorithms capable of handling a range of changing characteristics [2]. Another important example is forensics, in which intrinsic operational factors further degrade recognition performance.There are number of factors that can affect the quality of biometric signals, and there are numerous roles of a quality measure in the context of biometric systems. This section summarizes the state of the art in the biometric quality problem, giving an overall framework of the different challenges involved.
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| 13. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Super-Resolution for Selfie Biometrics : Introduction and Application to Face and Iris
- 2019. - 1
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Ingår i: Selfie Biometrics. - Cham : Springer. - 9783030269715 - 9783030269722 ; , s. 105-128
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Bokkapitel (refereegranskat)abstract
- Biometric research is heading towards enabling more relaxed acquisition conditions. This has effects on the quality and resolution of acquired images, severly affecting the accuracy of recognition systems if not tackled appropriately. In this chapter, we give an overview of recent research in super-resolution reconstruction applied to biometrics, with a focus on face and iris images in the visible spectrum, two prevalent modalities in selfie biometrics. After an introduction to the generic topic of super-resolution, we investigate methods adapted to cater for the particularities of these two modalities. By experiments, we show the benefits of incorporating super-resolution to improve the quality of biometric images prior to recognition. © Springer Nature AG 2019
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| 14. |
- Bigun, Josef, 1961-, et al.
(författare)
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Multimodal biometric authentication using quality signals in mobile communications
- 2003
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Ingår i: Proceedings - 12th International Conference on Image Analysis and Processing, ICIAP 2003. - Los Alamitos, USA : IEEE Computer Society. - 0769519482 ; , s. 2-11
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The elements of multimodal authentication along with system models are presented. These include the machine experts as well as machine supervisors. In particular fingerprint and speech based systems will serve as illustration of a mobile authentication application. A novel signal adaptive supervisor, based on the input biometric signal quality is evaluated. Experimental results on data collected from mobile telephones are reported demonstrating the benefits of the proposed scheme. © 2003 IEEE.
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| 15. |
- Fierrez-Aguilar, Julian, et al.
(författare)
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Discriminative multimodal biometric authentication based on quality measures
- 2005
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Ingår i: Pattern Recognition. - Oxford : Pergamon Press. - 0031-3203 .- 1873-5142. ; 38:5, s. 777-779
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Tidskriftsartikel (refereegranskat)abstract
- A novel score-level fusion strategy based on quality measures for multimodal biometric authentication is presented. In the proposed method, the fusion function is adapted every time an authentication claim is performed based on the estimated quality of the sensed biometric signals at this time. Experimental results combining written signatures and quality-labelled fingerprints are reported. The proposed scheme is shown to outperform significantly the fusion approach without considering quality signals. In particular, a relative improvement of approximately 20% is obtained on the publicly available MCYT bimodal database.
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| 16. |
- Fierrez-Aguilar, Julian, et al.
(författare)
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Kernel-based multimodal biometric verification using quality signals
- 2004
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Ingår i: Proceedings of SPIE. - : SPIE. ; , s. 544-554
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- A novel kernel-based fusion strategy is presented. It is based on SVM classifiers, trade-off coefficients introduced in the standard SVM training and testing procedures, and quality measures of the input biometric signals. Experimental results on a prototype application based on voice and fingerprint traits are reported. The benefits of using the two modalities as compared to only using one of them are revealed. This is achieved by using a novel experimental procedure in which multi-modal verification performance tests are compared with multi-probe tests of the individual subsystems. Appropriate selection of the parameters of the proposed quality-based scheme leads to a quality-based fusion scheme outperforming the raw fusion strategy without considering quality signals. In particular, a relative improvement of 18% is obtained for small SVM training set size by using only fingerprint quality labels.
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| 17. |
- Fierrez, Julian, et al.
(författare)
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BiosecurID : A Multimodal Biometric Database
- 2010
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Ingår i: Pattern Analysis and Applications. - New York, USA : Springer-Verlag New York. - 1433-7541 .- 1433-755X. ; 13:2, s. 235-246
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Tidskriftsartikel (refereegranskat)abstract
- A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol. The database includes eight unimodal biometric traits, namely: speech, iris, face (still images, videos of talking faces), handwritten signature and handwritten text (on-line dynamic signals, off-line scanned images), fingerprints (acquired with two different sensors), hand (palmprint, contour-geometry) and keystroking. The database comprises 400 subjects and presents features such as: realistic acquisition scenario, balanced gender and population distributions, availability of information about particular demographic groups (age, gender, handedness), acquisition of replay attacks for speech and keystroking, skilled forgeries for signatures, and compatibility with other existing databases. All these characteristics make it very useful in research and development of unimodal and multimodal biometric systems. © Springer-Verlag London Limited 2009.
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| 18. |
- Fronthaler, Hartwig, et al.
(författare)
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Fingerprint Image Quality Estimation and its Application to Multi-Algorithm Verification
- 2006
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Recently, image quality awareness has been found to increase recognition rates and to supportdecisions in multimodal authentication systems significantly. Nevertheless, automatic quality assessmentis still an open issue, especially with regard to biometric authentication tasks. Here we analyze theorientation tensor of fingerprint images with a set of symmetry descriptors, in order to detect fingerprintimage quality impairments like noise, lack of structure, blur, etc. Allowed classes of local shapes area priori application information for the proposed quality measures, therefore no training or explicitimage reference information is required. Our quality assessment method is compared to an existingautomatic method and a human opinion in numerous experiments involving several public databases.Once the quality of an image is determined, it can be exploited in several ways, one of which is toadapt fusion parameters in a monomodal multi-algorithm environment, here a number of fingerprintrecognition systems. In this work, several trained and non-trained fusion schemes applied to the scoresof these matchers are compared. A Bayes-based strategy for combining experts with weights on theirpast performances, able to readapt to each identity claim based on the input quality is developed andevaluated. To show some of the advantages of quality-driven multi-algorithm fusion, such as boostingrecognition rates, increasing computational efficiency, etc., a novel cascade fusion and simple fusionrules are employed in comparison as well.
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| 19. |
- Fronthaler, Hartwig, et al.
(författare)
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Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification
- 2008
-
Ingår i: IEEE Transactions on Information Forensics and Security. - New York, N.Y. : IEEE Signal Processing Society. - 1556-6013 .- 1556-6021. ; 3:2, s. 331-338
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Tidskriftsartikel (refereegranskat)abstract
- Signal-quality awareness has been found to increase recognition rates and to support decisions in multisensor environments significantly. Nevertheless, automatic quality assessment is still an open issue. Here, we study the orientation tensor of fingerprint images to quantify signal impairments, such as noise, lack of structure, blur, with the help of symmetry descriptors. A strongly reduced reference is especially favorable in biometrics, but less information is not sufficient for the approach. This is also supported by numerous experiments involving a simpler quality estimator, a trained method (NFIQ), as well as the human perception of fingerprint quality on several public databases. Furthermore, quality measurements are extensively reused to adapt fusion parameters in a monomodal multialgorithm fingerprint recognition environment. In this study, several trained and nontrained score-level fusion schemes are investigated. A Bayes-based strategy for incorporating experts' past performances and current quality conditions, a novel cascaded scheme for computational efficiency, besides simple fusion rules, is presented. The quantitative results favor quality awareness under all aspects, boosting recognition rates and fusing differently skilled experts efficiently as well as effectively (by training).
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| 20. |
- Galbally, Javier, et al.
(författare)
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A High Performance Fingerprint Liveness Detection Method Based on Quality Related Features
- 2012
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Ingår i: Future Generation Computer Systems. - Amsterdam : Elsevier. - 0167-739X .- 1872-7115. ; 28:1, s. 311-321
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Tidskriftsartikel (refereegranskat)abstract
- A new software-based liveness detection approach using a novel fingerprint parameterization based on quality related features is proposed. The system is tested on a highly challenging database comprising over 10,500 real and fake images acquired with five sensors of different technologies and covering a wide range of direct attack scenarios in terms of materials and procedures followed to generate the gummy fingers. The proposed solution proves to be robust to the multi-scenario dataset, and presents an overall rate of 90% correctly classified samples. Furthermore, the liveness detection method presented has the added advantage over previously studied techniques of needing just one image from a finger to decide whether it is real or fake. This last characteristic provides the method with very valuable features as it makes it less intrusive, more user friendly, faster and reduces its implementation costs. © 2010 Elsevier B.V. All rights reserved.
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| 21. |
- Galbally, Javier, et al.
(författare)
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Evaluation of Direct Attacks to Fingerprint Verification Systems
- 2011
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Ingår i: Telecommunications Systems. - New York : Springer-Verlag New York. - 1018-4864 .- 1572-9451. ; 47:3, s. 243-254
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Tidskriftsartikel (refereegranskat)abstract
- The vulnerabilities of fingerprint-based recognition systems to direct attacks with and without the cooperation of the user are studied. Two different systems, one minutiae-based and one ridge feature-based, are evaluated on a database of real and fake fingerprints. Based on the fingerprint images quality and on the results achieved on different operational scenarios, we obtain a number of statistically significant observations regarding the robustness of the systems. © 2010 Springer Science+Business Media, LLC.
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| 22. |
- Gonzalez-Sosa, Ester, et al.
(författare)
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Exploring Body Texture From mmW Images for Person Recognition
- 2019
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Ingår i: IEEE Transactions on Biometrics, Behavior, and Identity Science. - Piscataway, NJ : IEEE. - 2637-6407. ; 1:2, s. 139-151
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Tidskriftsartikel (refereegranskat)abstract
- Imaging using millimeter waves (mmWs) has many advantages including the ability to penetrate obscurants, such as clothes and polymers. After having explored shape information retrieved from mmW images for person recognition, in this paper we aim to gain some insight about the potential of using mmW texture information for the same task, considering not only the mmW face, but also mmW torso and mmW wholebody. We report experimental results using the mmW TNO database consisting of 50 individuals based on both hand-crafted and learned features from Alexnet and VGG-face pretrained convolutional neural networks (CNNs) models. First, we analyze the individual performance of three mmW body parts, concluding that: 1) mmW torso region is more discriminative than mmW face and the whole body; 2) CNN features produce better results compared to hand-crafted features on mmW faces and the entire body; and 3) hand-crafted features slightly outperform CNN features on mmW torso. In the second part of this paper, we analyze different multi-algorithmic and multi-modal techniques, including a novel CNN-based fusion technique, improving verification results to 2% EER and identification rank-1 results up to 99%. Comparative analyses with mmW body shape information and face recognition in the visible and NIR spectral bands are also reported.
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| 23. |
- Gonzalez-Sosa, Ester, et al.
(författare)
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Facial Soft Biometrics for Recognition in the Wild : Recent Works, Annotation and Evaluation
- 2018
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Ingår i: IEEE Transactions on Information Forensics and Security. - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 1556-6013 .- 1556-6021. ; 13:8, s. 2001-2014
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Tidskriftsartikel (refereegranskat)abstract
- The role of soft biometrics to enhance person recognition systems in unconstrained scenarios has not been extensively studied. Here, we explore the utility of the following modalities: gender, ethnicity, age, glasses, beard, and moustache. We consider two assumptions: 1) manual estimation of soft biometrics and 2) automatic estimation from two commercial off-the-shelf systems (COTS). All experiments are reported using the labeled faces in the wild (LFW) database. First, we study the discrimination capabilities of soft biometrics standalone. Then, experiments are carried out fusing soft biometrics with two state-of-the-art face recognition systems based on deep learning. We observe that soft biometrics is a valuable complement to the face modality in unconstrained scenarios, with relative improvements up to 40%/15% in the verification performance when using manual/automatic soft biometrics estimation. Results are reproducible as we make public our manual annotations and COTS outputs of soft biometrics over LFW, as well as the face recognition scores. © 2018 IEEE.
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| 24. |
- Krish, Ram P., et al.
(författare)
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Improving Automated Latent Fingerprint Identification Using Extended Minutia Types
- 2019
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Ingår i: Information Fusion. - Amsterdam : Elsevier. - 1566-2535 .- 1872-6305. ; 50, s. 9-19
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Tidskriftsartikel (refereegranskat)abstract
- Latent fingerprints are usually processed with Automated Fingerprint Identification Systems (AFIS) by law enforcement agencies to narrow down possible suspects from a criminal database. AFIS do not commonly use all discriminatory features available in fingerprints but typically use only some types of features automatically extracted by a feature extraction algorithm. In this work, we explore ways to improve rank identification accuracies of AFIS when only a partial latent fingerprint is available. Towards solving this challenge, we propose a method that exploits extended fingerprint features (unusual/rare minutiae) not commonly considered in AFIS. This new method can be combined with any existing minutiae-based matcher. We first compute a similarity score based on least squares between latent and tenprint minutiae points, with rare minutiae features as reference points. Then the similarity score of the reference minutiae-based matcher at hand is modified based on a fitting error from the least square similarity stage. We use a realistic forensic fingerprint casework database in our experiments which contains rare minutiae features obtained from Guardia Civil, the Spanish law enforcement agency. Experiments are conducted using three minutiae-based matchers as a reference, namely: NIST-Bozorth3, VeriFinger-SDK and MCC-SDK. We report significant improvements in the rank identification accuracies when these minutiae matchers are augmented with our proposed algorithm based on rare minutiae features. © 2018 Elsevier B.V.
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| 25. |
- Krish, Ram P., et al.
(författare)
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Partial Fingerprint Registration for Forensics using Minutiae-generated Orientation Fields
- 2014
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Ingår i: 2nd International Workshop on Biometrics and Forensics (IWBF2014). - Piscataway, NJ : IEEE Press. - 9781479943708
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Konferensbidrag (refereegranskat)abstract
- Minutia based matching scheme is the most widely accepted method for both automated as well as manual (forensic) fingerprint matching. The scenario of comparing a partial fingerprint minutia set against a full fingerprint minutia set is a challenging problem. In this work, we propose a method to register the orientation field of the partial fingerprint minutia set to that of the orientation field of full fingerprint minutia set. As a consequence of registering the partial fingerprint orientation field, we obtain extra information that can augment a minutia based matcher by reducing the search space of minutiae in the full fingerprint. We present the accuracy of our registration algorithm on NIST-SD27 database, reporting separately for both subjective and quantitative quality classification of NIST-SD27. The registration performance accuracy is measured in terms of percentage of ground truth minutiae present in the reduced minutiae search space generated by our algorithm. ©2014 IEEE.
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