Zhigang Yao

Literature review of fingerprint quality assessment and its evaluation

Fingerprint quality assessment (FQA) has been a challenging issue due to a variety of noisy information contained in the samples, such as physical defect and distortions caused by sensing devices. Existing studies have made efforts to find out more suitable techniques for assessing fingerprint quality but it is difficult to achieve a common solution because of, for example, different image settings. This study is two-fold, related to FQA, including a literature review of the prior work in assessing fingerprint image quality and the associated evaluation approaches. First, the authors categorised some representative studies proposed in last few decades to show how this problem has been solved so far. Second, this study gives a brief introduction of the associated evaluation approaches, and then contributes an extended evaluation framework based on the enrolment selection, which offers repeatable and statistically convincing measures for evaluating quality metrics. Experimental results demonstrate the usability of the proposed evaluation framework via offline trials.

Fingerprint Quality Assessment Combining Blind Image Quality, Texture and Minutiae Features

Biometric sample quality assessment approaches are generally designed in terms of utility property due to the potential difference between human perception of quality and the biometric quality requirements for a recognition system. This study proposes a utility based quality assessment method of fingerprints by considering several complementary aspects: 1) Image quality assessment without any reference which is consistent with human conception of inspecting quality, 2) Textural features related to the fingerprint image and 3) minutiae features which correspond to the most used information for matching. The proposed quality metric is obtained by a linear combination of these features and is validated with a reference metric using different approaches. Experiments performed on several trial databases show the benefit of the proposed fingerprint quality metric.

Quality assessment of fingerprints with minutiae delaunay triangulation

This article proposes a new quality assessment method of fingerprint, represented by only a set of minutiae points. The proposed quality metric is modeled with the convex-hull and Delaunay triangulation of the minutiae points. The validity of this quality metric is verified on several Fingerprint Verification Competition (FVC) databases by referring to an image-based metric from the state of the art (considered as the reference). The experiments of the utility-based evaluation approach demonstrate that the proposed quality metric is able to generate a desired result. We reveal the possibility of assessing fingerprint quality when only the minutiae template is available.

Fingerprint Quality Assessment with Multiple Segmentation

Image quality is an important factor for automated fingerprint identification systems (AFIS) because the matching performance could be significantly affected by poor quality samples. Most of the existing studies mainly focus on calculating a quality index via either a single feature or a combination of multiple features, and some others achieve this purpose with learning approaches which may depend on a prior-knowledge of matching performance. In this paper, a general framework for estimating fingerprint image quality is proposed by fusing features in segmentation phase. The quality index is indicated by a ratio of the pixel number of the integrated foreground area to the size (pixel number) of the fingerprint image. The potential advantage of this framework is that it could be improved by integrating other segmentation approaches or quality features rather than fusing them in a more complicated manner. The experiment is performed with several fingerprint datasets created via different sensors. Experimental results obtained from a dual evaluation approach demonstrate the validity of the proposed method in improving the overall performance.

EvaBio a New Modular Platform to Evaluate Biometric System

when someone wants to make a payment with a smartcard, the user has to enter a pin code to be identified. Only biometrics is able to authenticate a user; yet biometric information is sensitive. To ensure the security and privacy of biometric data, OCC (On-Card-Comparison) has been proposed. This approach consists in storing biometric data in a secure zone on a smartcard and computing the verification decision in a Secure Element (SE). The purpose of this paper is to propose an evaluation platform for testing biometric systems such as the analysis of performance and security on biometric OCC. Based on four examples, we illustrate its different uses in an operationnal context. The first example focus on the “Quality module” which allows to choose the enrollment by considering the fingerprint quality with one proposed metric. The second one addresses the minutiae reduction of the fingerprint template when the number of minutiae is higher than expected by the OCC. The third is based on sensors acquisition module to create databases and made attacks on sensors. The last one is the evaluation module, it permit to visualize results after an evaluation.

Fingerprint Quality Assessment: Matching Performance and Image Quality

This article chiefly focuses on Fingerprint Quality Assessment (FQA) applied to the Automatic Fingerprint Identification System (AFIS). In our research work, different FQA solutions proposed so far are compared by using several quality metrics selected from the existing studies. The relationship between the quality metric and the matching performance is specifically analyzed via such a comparison and an extra discussion based on the sample utility. This study is achieved via an interoperability analysis by using two different matching tools. Experimental results represented by the global Equal Error Rate (EER) further reveal the constraint of the existing quality assessment solutions in predicting the matching performance. Experiments are performed via several public-known fingerprint databases.

Blind minutiae selection for standard minutiae templates

The embedded applications of fingerprint proposed so far are chiefly based on the minutiae template. This kind of system is not resource-free and minutiae template is generally sacrificed to cover the shortage. This paper presents several simple yet efficient no-image minutiae selection approaches (NIMS) for the standard minutiae templates (ISO/IEC 19794-2). With the reduced-templates obtained by using the proposed methods, the overall performance can be guaranteed in comparing with the results generated by the original templates. The interoperability tests are performed with several FVC databases. An additional analysis with the quality of the enrollment samples is also carried out. The experimental results demonstrate the validity and efficiency of the proposed approaches.