| 1. |
- 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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| 2. |
- 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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| 3. |
- 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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| 4. |
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| 5. |
- 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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| 6. |
- 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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| 7. |
- Fronthaler, Hartwig, et al.
(författare)
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Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification
- 2008
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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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| 8. |
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| 9. |
- Poh, Norman, et al.
(författare)
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Benchmarking Quality-dependent and Cost-sensitive Score-level Multimodal Biometric Fusion Algorithms
- 2009
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Ingår i: IEEE Transactions on Information Forensics and Security. - Piscataway, N.J. : IEEE Press. - 1556-6013 .- 1556-6021. ; 4:4, s. 849-866
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Tidskriftsartikel (refereegranskat)abstract
- Automatically verifying the identity of a person by means of biometrics (e.g., face and fingerprint) is an important application in our day-to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are often used. Such a combined system is known as a multimodal biometric system. This paper reports a benchmarking study carried out within the framework of the BioSecure DS2 (Access Control) evaluation campaign organized by the University of Surrey, involving face, fingerprint, and iris biometrics for person authentication, targeting the application of physical access control in a medium-size establishment with some 500 persons. While multimodal biometrics is a well-investigated subject in the literature, there exists no benchmark for a fusion algorithm comparison. Working towards this goal, we designed two sets of experiments: quality-dependent and cost-sensitive evaluation. The quality-dependent evaluation aims at assessing how well fusion algorithms can perform under changing quality of raw biometric images principally due to change of devices. The cost-sensitive evaluation, on the other hand, investigates how well a fusion algorithm can perform given restricted computation and in the presence of software and hardware failures, resulting in errors such as failure-to-acquire and failure-to-match. Since multiple capturing devices are available, a fusion algorithm should be able to handle this nonideal but nevertheless realistic scenario. In both evaluations, each fusion algorithm is provided with scores from each biometric comparison subsystem as well as the quality measures of both the template and the query data. The response to the call of the evaluation campaign proved very encouraging, with the submission of 22 fusion systems. To the best of our knowledge, this campaign is the first attempt to benchmark quality-based multimodal fusion algorithms. In the presence of changing image quality which may be due to a change of acquisition devices and/or device capturing configurations, we observe that the top performing fusion algorithms are those that exploit automatically derived quality measurements. Our evaluation also suggests that while using all the available biometric sensors can definitely increase the fusion performance, this comes at the expense of increased cost in terms of acquisition time, computation time, the physical cost of hardware, and its maintenance cost. As demonstrated in our experiments, a promising solution which minimizes the composite cost is sequential fusion, where a fusion algorithm sequentially uses match scores until a desired confidence is reached, or until all the match scores are exhausted, before outputting the final combined score. © 2009 IEEE.
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