| 1. |
- Bigun, Josef, 1961-, et al.
(författare)
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Recognition by symmetry derivatives and the generalized structure tensor
- 2004
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Ingår i: IEEE Transactions on Pattern Analysis and Machine Intelligence. - Los Alamitos, USA : IEEE Computer Society. - 0162-8828 .- 1939-3539. ; 26:12, s. 1590-1605
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Tidskriftsartikel (refereegranskat)abstract
- We suggest a set of complex differential operators that can be used to produce and filter dense orientation (tensor) fields for feature extraction, matching, and pattern recognition. We present results on the invariance properties of these operators, that we call symmetry derivatives. These show that, in contrast to ordinary derivatives, all orders of symmetry derivatives of Gaussians yield a remarkable invariance: they are obtained by replacing the original differential polynomial with the same polynomial, but using ordinary coordinates x and y corresponding to partial derivatives. Moreover, the symmetry derivatives of Gaussians are closed under the convolution operator and they are invariant to the Fourier transform. The equivalent of the structure tensor, representing and extracting orientations of curve patterns, had previously been shown to hold in harmonic coordinates in a nearly identical manner. As a result, positions, orientations, and certainties of intricate patterns, e.g., spirals, crosses, parabolic shapes, can be modeled by use of symmetry derivatives of Gaussians with greater analytical precision as well as computational efficiency. Since Gaussians and their derivatives are utilized extensively in image processing, the revealed properties have practical consequences for local orientation based feature extraction. The usefulness of these results is demonstrated by two applications:tracking cross markers in long image sequences from vehicle crash tests andalignment of noisy fingerprints.
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| 2. |
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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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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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| 5. |
- 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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| 6. |
- 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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| 7. |
- 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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| 8. |
- 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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| 9. |
- 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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| 10. |
- Alonso-Fernandez, Fernando, 1978-, et al.
(författare)
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Compact Multi-scale Periocular Recognition Using SAFE Features
- 2016
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Ingår i: Proceedings - International Conference on Pattern Recognition. - Washington : IEEE. - 9781509048472 ; , s. 1455-1460
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present a new approach for periocular recognition based on the Symmetry Assessment by Feature Expansion (SAFE) descriptor, which encodes the presence of various symmetric curve families around image key points. We use the sclera center as single key point for feature extraction, highlighting the object-like identity properties that concentrates to this unique point of the eye. As it is demonstrated, such discriminative properties can be encoded with a reduced set of symmetric curves. Experiments are done with a database of periocular images captured with a digital camera. We test our system against reference periocular features, achieving top performance with a considerably smaller feature vector (given by the use of a single key point). All the systems tested also show a nearly steady correlation between acquisition distance and performance, and they are also able to cope well when enrolment and test images are not captured at the same distance. Fusion experiments among the available systems are also provided. © 2016 IEEE
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