A review of schemes for fingerprint image quality computation

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.Comment: Published at 3rd COST-275 Workshop on Biometrics on the Internet. arXiv admin note: text overlap with arXiv:2111.0743

On the Effects of Image Quality Degradation on Minutiae- and Ridge-Based Automatic Fingerprint Recognition

The effect of image quality degradation on the verification performance of automatic fingerprint recognition is investigated. We study the performance of two fingerprint matchers based on minutiae and ridge information under varying fingerprint image quality. The ridge-based system is found to be more robust to image quality degradation than the minutiae-based system for a number of different image quality criteria.Comment: Published at IEEE International Carnahan Conference on Security Technology (ICCST

A Review Of Schemes For Fingerprint Image Quality Computation

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

Target Dependent Score Normalization . . .

Score normalization method in biometric verification, which encompass the more tradEy%RBB user-d%RBB9By dser-d thresholdBP techniques, are reviewed from a test hypotheses point of view. These are classified into testdsty6EPB and targetdtyE7x7x method7 The focus of the paper is on targetdty6H6EP score normalization techniques, which are further classified into impostor-centric, target-centric,and target-impostormethodo These areapplied to an on-line signature verification system on signatured6B from the First International Signature Verification Competition (SVC 2004). In particular, a target-centric technique based on the cross-validy6B6 procedE e providB the best relative performance improvement testing both with skilled (19%) and randy forgeries (53%) as compared to the raw verification performance without score normalization (7.14% and 1.06% Equal Error Rate for skilled and random forgeries, respectively)

Sensor Interoperability and Fusion in Signature Verification: A Case Study . . .

Several works related to information fusion for signature verification have been presented. However, few works have focused on sensor fusion and sensor interoperability. In this paper, these two topics are evaluated for signature verification using two di#erent commercial Tablet PCs. An enrolment strategy using signatures from the two Tablet PCs is also proposed. Authentication performance experiments are reported by using a database with over 3000 signatures

Fingerprint Anti-spoofing in Biometric Systems

This chapter is focused on giving a comprehensive description of the state-of-the-art in biometric-based fingerprint anti-spoofing and the big advances that have been reached in this field over the last decade. In addition, after a comprehensive review of the available literature in the field, we explore the potential of quality assessment as a way to enhance the security of the fingerprint-based technology against direct attacks. We believe that, beyond the interest that the described techniques intrinsically have, the case study presented may serve as an example of how to develop and validate fingerprint anti-spoofing techniques based on common and publicly available benchmarks and following a systematic and replicable protocol

On-line signature verification resilience to packet loss in IP networks

This paper reports on experiments investigating the effects of packet loss for two online signature verification systems distributed over the Internet. The effects on verification performance of using different signature data recovery strategies are explored. Justifications are given taking into account the statistical nature of the signature models used for the verification task. Under realistic packet loss conditions, it is found that marginalising the lost feature vectors at the verification stage outperforms other feature-based data imputation methods such as packet repetition

Using Quality Measures for Multilevel Speaker Recognition

The use of quality information for multilevel speaker recognition systems is addressed in this contribution. From a definition of what constitutes a quality measure, two applications are proposed at different phases of the recognition process: scoring and multi-level fusion stages. The traditional likelihood scoring stage is further developed providing guidelines for the practical application of the proposed ideas. Conventional user-independent multilevel Support Vector Machine (SVM) score fusion is also adapted for the inclusion of quality information in the fusion process. In particular, quality measures meeting three different goodness criteria: SNR, F0 deviations and the ITUP.563 objective speech quality assessment are used in the speaker recognition process. Experiments carried out in the Switchboard-I database assess the benefits of the proposed quality-guided recognition approach for both the score computation and score fusion stages