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| 2. |
- Alfakir, Omar, et al.
(författare)
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A Cross-Platform Mobile Application for Ambulance CPR during Cardiac Arrests
- 2021
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Ingår i: 2021 8th International Conference on Soft Computing & Machine Intelligence (ISCMI). - Piscataway : IEEE. - 9781728186832 - 9781728186825 - 9781728186849 ; , s. 120-124
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Konferensbidrag (refereegranskat)abstract
- This paper describes the implementation of a cross-platform software application to aid ambulance paramedics during CPR (Cardio-Pulmonary Resuscitation). It must be able to work both on iOS and Android devices, which are the leading platforms in the mobile industry. The goal of the application is to guide paramedics in the different processes and expected medication to be administered during a cardiac arrest, a scenario that is usually stressful and fast-paced, thus prone to errors or distractions. The tool must provide timely reminders of the different actions to be performed during a cardiac arrest, and in an appropriate order, based on the results of the previous actions. A timer function will also control the duration of each step of the CPR procedure. The application is implemented in React Native which, using JavaScript as programming language, allows to deploy applications that can run both in iOS and Android native languages. Our solution could also serve as a record of events that could be transmitted (even in real-time) to the hospital without demanding explicit verbal communication of the procedures or medications administered to the patient during the ambulance trip. This would provide even higher efficiency in the process, and would allow automatic incorporation of the events to the medical record of the patient as well. © 2021 IEEE.
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| 3. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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A Comparative Study of Fingerprint Image-Quality Estimation Methods
- 2007
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Ingår i: IEEE Transactions on Information Forensics and Security. - New York : IEEE Press. - 1556-6013 .- 1556-6021. ; 2:4, s. 734-743
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Tidskriftsartikel (refereegranskat)abstract
- One of the open issues in fingerprint verification is the lack of robustness against image-quality degradation. Poor-quality images result in spurious and missing features, thus degrading the performance of the overall system. Therefore, it is important for a fingerprint recognition system to estimate the quality and validity of the captured fingerprint images. In this work, we review existing approaches for fingerprint image-quality estimation, including the rationale behind the published measures and visual examples showing their behavior under different quality conditions. We have also tested a selection of fingerprint image-quality estimation algorithms. For the experiments, we employ the BioSec multimodal baseline corpus, which includes 19 200 fingerprint images from 200 individuals acquired in two sessions with three different sensors. The behavior of the selected quality measures is compared, showing high correlation between them in most cases. The effect of low-quality samples in the verification performance is also studied for a widely available minutiae-based fingerprint matching system.
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| 4. |
- 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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| 5. |
- 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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| 6. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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A survey on periocular biometrics research
- 2016
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Ingår i: Pattern Recognition Letters. - Amsterdam : Elsevier. - 0167-8655 .- 1872-7344. ; 82, part 2, s. 92-105
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Tidskriftsartikel (refereegranskat)abstract
- Periocular refers to the facial region in the vicinity of the eye, including eyelids, lashes and eyebrows. While face and irises have been extensively studied, the periocular region has emerged as a promising trait for unconstrained biometrics, following demands for increased robustness of face or iris systems. With a surprisingly high discrimination ability, this region can be easily obtained with existing setups for face and iris, and the requirement of user cooperation can be relaxed, thus facilitating the interaction with biometric systems. It is also available over a wide range of distances even when the iris texture cannot be reliably obtained (low resolution) or under partial face occlusion (close distances). Here, we review the state of the art in periocular biometrics research. A number of aspects are described, including: (i) existing databases, (ii) algorithms for periocular detection and/or segmentation, (iii) features employed for recognition, (iv) identification of the most discriminative regions of the periocular area, (v) comparison with iris and face modalities, (vi) soft-biometrics (gender/ethnicity classification), and (vii) impact of gender transformation and plastic surgery on the recognition accuracy. This work is expected to provide an insight of the most relevant issues in periocular biometrics, giving a comprehensive coverage of the existing literature and current state of the art. © 2015 Elsevier B.V. All rights reserved.
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| 7. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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An Explainable Model-Agnostic Algorithm for CNN-Based Biometrics Verification
- 2023
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Ingår i: 2023 IEEE International Workshop on Information Forensics and Security (WIFS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350324914
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Konferensbidrag (refereegranskat)abstract
- This paper describes an adaptation of the Local Interpretable Model-Agnostic Explanations (LIME) AI method to operate under a biometric verification setting. LIME was initially proposed for networks with the same output classes used for training, and it employs the softmax probability to determine which regions of the image contribute the most to classification. However, in a verification setting, the classes to be recognized have not been seen during training. In addition, instead of using the softmax output, face descriptors are usually obtained from a layer before the classification layer. The model is adapted to achieve explainability via cosine similarity between feature vectors of perturbated versions of the input image. The method is showcased for face biometrics with two CNN models based on MobileNetv2 and ResNet50. © 2023 IEEE.
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| 8. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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An Overview of Periocular Biometrics
- 2017
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Ingår i: Iris and Periocular Biometric Recognition. - London : The Institution of Engineering and Technology. - 9781785611681 - 9781785611698 ; , s. 29-53
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Bokkapitel (refereegranskat)abstract
- Periocular biometrics specifically refers to the externally visible skin region of the face that surrounds the eye socket. Its utility is specially pronounced when the iris or the face cannot be properly acquired, being the ocular modality requiring the least constrained acquisition process. It appears over a wide range of distances, even under partial face occlusion (close distance) or low resolution iris (long distance), making it very suitable for unconstrained or uncooperative scenarios. It also avoids the need of iris segmentation, an issue in difficult images. In such situation, identifying a suspect where only the periocular region is visible is one of the toughest real-world challenges in biometrics. The richness of the periocular region in terms of identity is so high that the whole face can even be reconstructed only from images of the periocular region. The technological shift to mobile devices has also resulted in many identity-sensitive applications becoming prevalent on these devices.
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| 9. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Best Regions for Periocular Recognition with NIR and Visible Images
- 2014
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Ingår i: 2014 IEEE International Conference on Image Processing (ICIP). - Piscataway, NJ : IEEE Press. - 9781479957514 ; , s. 4987-4991
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Konferensbidrag (refereegranskat)abstract
- We evaluate the most useful regions for periocular recognition. For this purpose, we employ our periocular algorithm based on retinotopic sampling grids and Gabor analysis of the spectrum. We use both NIR and visible iris images. The best regions are selected via Sequential Forward Floating Selection (SFFS). The iris neighborhood (including sclera and eyelashes) is found as the best region with NIR data, while the surrounding skin texture (which is over-illuminated in NIR images) is the most discriminative region in visible range. To the best of our knowledge, only one work in the literature has evaluated the influence of different regions in the performance of periocular recognition algorithms. Our results are in the same line, despite the use of completely different matchers. We also evaluate an iris texture matcher, providing fusion results with our periocular system as well. © 2014 IEEE.
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| 10. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Biometric Recognition Using Periocular Images
- 2013
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We present a new system for biometric recognition using periocular images based on retinotopic sampling grids and Gabor analysis of the local power spectrum at different frequencies and orientations. A number of aspects are studied, including: 1) grid adaptation to dimensions of the target eye vs. grids of constant size, 2) comparison between circular- and rectangular-shaped grids, 3) use of Gabor magnitude vs. phase vectors for recognition, and 4) rotation compensation between query and test images. Results show that our system achieves competitive verification rates compared with other periocular recognition approaches. We also show that top verification rates can be obtained without rotation compensation, thus allowing to remove this step for computational efficiency. Also, the performance is not affected substantially if we use a grid of fixed dimensions, or it is even better in certain situations, avoiding the need of accurate detection of the iris region.
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