Quality Assessment of Biometric Systems: A Comprehensive Perspective Based on Accuracy and Performance Measurement

Gamassi, Marco; Lazzaroni, M.; Misino, M.; Piuri, Vincenzo; Sana, D.; Scotti, Fabio

doi:10.1109/tim.2005.851087

Cited by 44 publications

(26 citation statements)

References 16 publications

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“…Discriminative methods are also sensitive to noise. It remains an interesting topic for future work to develop and analyze the accuracy of a discriminative dictionary learning algorithm that is robust to pose, expression and illumination variations [49]. …”

Section: Discussionmentioning

confidence: 99%

Dictionary-Based Face Recognition Under Variable Lighting and Pose

Patel

Biswas

et al. 2012

IEEE Trans.Inform.Forensic Secur.

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Abstract-We present a face recognition algorithm based on simultaneous sparse approximations under varying illumination and pose. A dictionary is learned for each class based on given training examples which minimizes the representation error with a sparseness constraint. A novel test image is projected onto the span of the atoms in each learned dictionary. The resulting residual vectors are then used for classification. To handle variations in lighting conditions and pose, an image relighting technique based on pose-robust albedo estimation is used to generate multiple frontal images of the same person with variable lighting. As a result, the proposed algorithm has the ability to recognize human faces with high accuracy even when only a single or a very few images per person are provided for training. The efficiency of the proposed method is demonstrated using publicly available databases and it is shown that this method is efficient and can perform significantly better than many competitive face recognition algorithms.

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Section: Discussionmentioning

confidence: 99%

Dictionary-Based Face Recognition Under Variable Lighting and Pose

Patel

Biswas

et al. 2012

IEEE Trans.Inform.Forensic Secur.

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“…15. From the curves, the Equal Error Rate (EER) with 95% confi- dence interval of our algorithm is 2.68±0.18% assuming uncorrelated matching decisions [51], [52]. The threshold at the EER point is approximately 0.420.…”

Section: Fingerprint Verification Based On Combined Featuresmentioning

confidence: 94%

Fingerprint Verification and Identification Based on Local Geometric Invariants Constructed from Minutiae Points and Augmented with Global Directional Filterbank Features

Pintavirooj

Cohen

Iampa

2014

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper addresses the problems of fingerprint identification and verification when a query fingerprint is taken under conditions that differ from those under which the fingerprint of the same person stored in a database was constructed. This occurs when using a different fingerprint scanner with a different pressure, resulting in a fingerprint impression that is smeared and distorted in accordance with a geometric transformation (e.g., affine or even non-linear). Minutiae points on a query fingerprint are matched and aligned to those on one of the fingerprints in the database, using a set of absolute invariants constructed from the shape and/or size of minutiae triangles depending on the assumed map. Once the best candidate match is declared and the corresponding minutiae points are flagged, the query fingerprint image is warped against the candidate fingerprint image in accordance with the estimated warping map. An identification/verification cost function using a combination of distance map and global directional filterbank (DFB) features is then utilized to verify and identify a query fingerprint against candidate fingerprint(s). Performance of the algorithm yields an area of 0.99967 (perfect classification is a value of 1) under the receiver operating characteristic (ROC) curve based on a database consisting of a total of 1680 fingerprint images captured from 240 fingers. The average probability of error was found to be 0.713%. Our algorithm also yields the smallest false non-match rate (FNMR) for a comparable false match rate (FMR) when compared to the well-known technique of DFB features and triangulation-based matching integrated with modeling non-linear deformation. This work represents an advance in resolving the fingerprint identification problem beyond the state-of-the-art approaches in both performance and robustness.

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“…Differently from traditional procedures used for the accuracy evaluation of biometric recognition algorithms, which do not consider the time passed between biometric acquisitions [24], this test permits to analyze the stability and persistency of the used features during a defined time interval. In this test, we have not used samples considered as FTA since it only aims to evaluate the persistency of PPG DET curve obtained on DB 15m .…”

Section: B Preliminary Test In Continuous Authentication Scenariosmentioning

confidence: 99%

A preliminary study on continuous authentication methods for photoplethysmographic biometrics

Bonissi

Labati

Perico

et al. 2013

2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications

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With respect to other physiological signals, PPG data present some advantages since they can be captured using widely diffused, comfortable, and low-cost sensors.In this paper, we present a feasibility study on continuous authentication techniques based on PPG signals. A biometric recognition method based on a correlation approach is first presented. Then, the accuracy of this method is evaluated on different datasets describing signals of variable time duration. Finally, the performance of continuous enrollment strategies are investigated.The obtained results suggest that PPG signals present sufficient discriminability to be used in biometric applications that do not require very high accuracy. Moreover, the use of continuous enrollment strategies can improve the performance of continuous authentication systems.

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Quality Assessment of Biometric Systems: A Comprehensive Perspective Based on Accuracy and Performance Measurement

Cited by 44 publications

References 16 publications

Dictionary-Based Face Recognition Under Variable Lighting and Pose

Dictionary-Based Face Recognition Under Variable Lighting and Pose

Fingerprint Verification and Identification Based on Local Geometric Invariants Constructed from Minutiae Points and Augmented with Global Directional Filterbank Features

A preliminary study on continuous authentication methods for photoplethysmographic biometrics

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