| 1. |
- 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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| 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. |
- Fronthaler, Hartwig, et al.
(författare)
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Pyramid-based Image Enhancement of Fingerprints
- 2007
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Ingår i: 2007 IEEE Workshop on Automatic Identification Advanced Technologies proceedings : 7-8 June 2007, Alghero, Italy. - Piscataway, NJ. : IEEE Press. - 1424413001 ; , s. 45-50
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Konferensbidrag (refereegranskat)abstract
- Reliable feature extraction is crucial for accurate biometric recognition. Unfortunately feature extraction is hampered by noisy input data, especially so in case of fingerprints. We propose a method to enhance the quality of a given fingerprint with the purpose to improve the recognition performance. A Laplacian like image-scale pyramid is used for this purpose to decompose the original fingerprint into 3 smaller images corresponding to different frequency bands. In a further step, contextual filtering is performed using these pyramid levels and 1D Gaussians, where the corresponding filtering directions are derived from the frequency-adapted structure tensor. All image processing is done in the spatial domain, avoiding block artifacts while conserving the biometric signal well. We report on comparative results and present quantitative improvements, by applying the standardized NIST FIS2 fingerprint matcher to the FVC2004 fingerprint database along with our as well as two other enhancements. The study confirms that the suggested enhancement robustifies feature detection, e.g. minutiae, which in turn improves the recognition (20% relative improvement in equal error rate on DB3 of FVC2004).
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| 4. |
- Kollreider, Klaus, et al.
(författare)
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Real-Time Face Detection and Motion Analysis With Application in “Liveness” Assessment
- 2007
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Ingår i: IEEE Transactions on Information Forensics and Security. - New York : IEEE Press. - 1556-6013 .- 1556-6021. ; 2:3 part 2, s. 548-558
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Tidskriftsartikel (refereegranskat)abstract
- A robust face detection technique along with mouth localization, processing every frame in real time (video rate), is presented. Moreover, it is exploited for motion analysis onsite to verify "liveness" as well as to achieve lip reading of digits. A methodological novelty is the suggested quantized angle features ("quangles") being designed for illumination invariance without the need for preprocessing (e.g., histogram equalization). This is achieved by using both the gradient direction and the double angle direction (the structure tensor angle), and by ignoring the magnitude of the gradient. Boosting techniques are applied in a quantized feature space. A major benefit is reduced processing time (i.e., that the training of effective cascaded classifiers is feasible in very short time, less than 1 h for data sets of order 104). Scale invariance is implemented through the use of an image scale pyramid. We propose "liveness" verification barriers as applications for which a significant amount of computation is avoided when estimating motion. Novel strategies to avert advanced spoofing attempts (e.g., replayed videos which include person utterances) are demonstrated. We present favorable results on face detection for the YALE face test set and competitive results for the CMU-MIT frontal face test set as well as on "liveness" verification barriers.
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| 5. |
- Kollreider, Klaus, et al.
(författare)
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Real-Time Face Detection Using Illumination Invariant Features
- 2007
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Ingår i: Image Analysis. - Berlin : Springer. - 9783540730392 ; , s. 41-50
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Konferensbidrag (refereegranskat)abstract
- A robust object/face detection technique processing every frame in real-time (video-rate) is presented. A methodological novelty are the suggested quantized angle features (“quangles”), being designed for illumination invariance without the need for pre-processing, e.g. histogram equalization. This is achieved by using both the gradient direction and the double angle direction (the structure tensor angle), and by ignoring the magnitude of the gradient. Boosting techniques are applied in a quantized feature space. Separable filtering and the use of lookup tables favor the detection speed. Furthermore, the gradient may then be reused for other tasks as well. A side effect is that the training of effective cascaded classifiers is feasible in very short time, less than 1 hour for data sets of order 104. We present favorable results on face detection, for several public databases (e.g. 93% Detection Rate at 1×10− 6 False Positive Rate on the CMU-MIT frontal face test set).
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