Quality Measures in Biometric Systems

• URL: http://arxiv.org/abs/2111.08704v1
• Date: Wed, 17 Nov 2021 13:28:07 GMT
• Title: Quality Measures in Biometric Systems
• Authors: Fernando Alonso-Fernandez, Julian Fierrez, Javier Ortega-Garcia
• Abstract summary: Quality is a critical issue in security, especially in adverse scenarios involving surveillance cameras, forensics, portable devices, or remote access through the Internet. This article analyzes what factors negatively impact biometric quality, how to overcome them, and how to incorporate quality measures into biometric systems.
• Score: 67.6699940572256
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Biometric technology has been increasingly deployed in the past decade, offering greater security and convenience than traditional methods of personal recognition. Although biometric signals' quality heavily affects a biometric system's performance, prior research on evaluating quality is limited. Quality is a critical issue in security, especially in adverse scenarios involving surveillance cameras, forensics, portable devices, or remote access through the Internet. This article analyzes what factors negatively impact biometric quality, how to overcome them, and how to incorporate quality measures into biometric systems. A review of the state of the art in these matters gives an overall framework for the challenges of biometric quality.

Related papers

• Long-Range Biometric Identification in Real World Scenarios: A Comprehensive Evaluation Framework Based on Missions [11.557368031775717]
  This paper evaluates research solutions for identifying individuals at ranges and altitudes. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification.
  arXiv  Detail & Related papers  (2024-09-03T02:17:36Z)
• ECS -- an Interactive Tool for Data Quality Assurance [63.379471124899915]
  We present a novel approach for the assurance of data quality. For this purpose, the mathematical basics are first discussed and the approach is presented using multiple examples. This results in the detection of data points with potentially harmful properties for the use in safety-critical systems.
  arXiv  Detail & Related papers  (2023-07-10T06:49:18Z)
• Fingerprint Image-Quality Estimation and its Application to Multialgorithm Verification [56.128200319868526]
  Signal-quality awareness has been found to increase recognition rates and to support decisions in multisensor environments significantly. Here, we study the orientation tensor of fingerprint images to quantify signal impairments, such as noise, lack of structure, blur, with the help of symmetry descriptors. The quantitative results favor quality awareness under all aspects, boosting recognition rates and fusing differently skilled experts efficiently as well as effectively.
  arXiv  Detail & Related papers  (2022-11-24T12:17:49Z)
• Quality-Based Conditional Processing in Multi-Biometrics: Application to Sensor Interoperability [63.05238390013457]
  We describe and evaluate the ATVS-UAM fusion approach submitted to the quality-based evaluation of the 2007 BioSecure Multimodal Evaluation Campaign. Our approach is based on linear logistic regression, in which fused scores tend to be log-likelihood-ratios. Results show that the proposed approach outperforms all the rule-based fusion schemes.
  arXiv  Detail & Related papers  (2022-11-24T12:11:22Z)
• Evaluation of User Perception on Biometric Fingerprint System [0.0]
  Biometric systems involve security assurance to make our system highly secured and robust. Several innovative system have been introduced, and most of them have biometrics installed to protect military bases, banking machines, and other sophisticated systems. Despite the benefits and enhancements in security that biometrics offer, there are also some vulnerabilities.
  arXiv  Detail & Related papers  (2022-05-21T23:39:07Z)
• Benchmarking Quality-Dependent and Cost-Sensitive Score-Level Multimodal Biometric Fusion Algorithms [58.156733807470395]
  This paper reports a benchmarking study carried out within the framework of the BioSecure DS2 (Access Control) evaluation campaign. The campaign targeted the application of physical access control in a medium-size establishment with some 500 persons. To the best of our knowledge, this is the first attempt to benchmark quality-based multimodal fusion algorithms.
  arXiv  Detail & Related papers  (2021-11-17T13:39:48Z)
• The Reliability and Acceptance of Biometric System in Bangladesh: Users Perspective [0.0]
  The study shows that users are satisfied by using biometric systems rather than other security systems. As system reliability and user satisfaction are the focused issue of this research, biometric service providers can use these phenomena to find what aspect of improvement they need for their services.
  arXiv  Detail & Related papers  (2021-06-14T08:46:00Z)
• Biometrics: Trust, but Verify [49.9641823975828]
  Biometric recognition has exploded into a plethora of different applications around the globe. There are a number of outstanding problems and concerns pertaining to the various sub-modules of biometric recognition systems.
  arXiv  Detail & Related papers  (2021-05-14T03:07:25Z)
• Biometric Quality: Review and Application to Face Recognition with FaceQnet [16.791628175513637]
  Quality is the number one factor responsible for the good or bad performance of automated biometric systems. Some of the most used and deployed biometric characteristics are lacking behind in the development of these methods. FaceQnet is a novel open-source face quality assessment tool, inspired and powered by deep learning technology.
  arXiv  Detail & Related papers  (2020-06-05T08:33:22Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.