| 1. |
|
|
| 2. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
-
A Review Of Schemes For Fingerprint Image Quality Computation
- 2005
-
Ingår i: COST Action 275. - Luxembourg : EU Publications Office (OPOCE). - 9789289800198 ; , s. 3-6
-
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.
|
|
| 3. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
-
A Survey of Super-Resolution in Iris Biometrics with Evaluation of Dictionary-Learning
- 2019
-
Ingår i: IEEE Access. - Piscataway, NJ : IEEE. - 2169-3536. ; 7, s. 6519-6544
-
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.
|
|
| 4. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
-
Combining multiple matchers for fingerprint verification : A case study in biosecure network of excellence
- 2007
-
Ingår i: Annales des télécommunications. - Paris, France : Springer. - 0003-4347 .- 1958-9395. ; 62:1-2, s. 62-82
-
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.
|
|
| 5. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
-
Cross-sensor periocular biometrics in a global pandemic : Comparative benchmark and novel multialgorithmic approach
- 2022
-
Ingår i: Information Fusion. - Amsterdam : Elsevier. - 1566-2535 .- 1872-6305. ; 83-84, s. 110-130
-
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
|
|
| 6. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
-
Fingerprint Databases and Evaluation
- 2015. - 2
-
Ingår i: Encyclopedia of Biometrics. - New York : Springer Science+Business Media B.V.. - 9781489974877 - 9781489974884 ; , s. 599-606
-
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.
|
|
| 7. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
-
Fingerprint Recognition
- 2009
-
Ingår i: Guide to Biometric Reference Systems and Performance Evaluation. - London : Springer London. - 9781848002913 - 9781848002920 ; , s. 51-88
-
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.
|
|
| 8. |
|
|
| 9. |
- Alonso-Fernandez, Fernando, et al.
(författare)
-
Quality-Based Conditional Processing in Multi-Biometrics : Application to Sensor Interoperability
- 2010
-
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
-
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.
|
|
| 10. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
-
Quality Measures in Biometric Systems
- 2012
-
Ingår i: IEEE Security and Privacy. - New York, NY : IEEE Computer Society. - 1540-7993 .- 1558-4046. ; 10:6, s. 52-62
-
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.
|
|
