(2012) Whats missing in biometric testing
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Panel presentation on "What is missing in Biometric Testing". Other panel presentations are available on the NIST IBPC website.
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In this research, intra-visit match score stability was examined for the human iris. Scores were found to be statistically stable in this short time frame.
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According to a report by Frost and Sullivan in 2007, revenues for non-AFIS fingerprint devices in notebook PC's and wireless devices is anticipated to grow from $148.5 million to $1588.0 million by 2014, a compound annual growth rate of 40.3% [1]. The AFIS market has a compound annual growth rate of 15.2% with revenues of $445.0 million in 2007. With the development of mobile applications in a number of different market segments, such as healthcare, retail, and law enforcement, this paper analyzed the performance of fingerprints of different sizes, from different sensors...(2013) The Role of Test Administrator and Error
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As the use of signatures for identification purposes is pervasive in society and has a long history in business, dynamic signature verification (DSV) could be an answer to authenticating a document signed electronically and establishing the identity of that document in a dispute. DSV has the advantage in that traits of the signature can be collected on a digitizer. The research question of this paper is to understand how the individual variables vary across devices. In applied applications, this is important because if the signature variables change across the digitizers this will impact performance and the ability to use those variable. Understanding which traits are consistent across devices will aid dynamic signature algorithm designers to create more robust algorithms.More from International Center for Biometric Research (11)
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(2012) Whats missing in biometric testing
- 1. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation BIOMETRIC TESTING – PANEL DISCUSSION STEPHEN ELLIOTT IPBC 2012 – 3/7/2012
- 2. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation WHAT IS MISSING IN BIOMETRIC TESTING
- 3. BIOMETRIC TESTING • Traditional biometric testing – Algorithm testing • Well established metrics • Well understood testing methodologies • Operational testing – Harder to do • Access to environments • Test methodologies dependent in some cases on the test
- 4. TESTING AND EVALUATION • Essentially trying to understand how a system performs – Maybe more fundamentally – who or what is causing the errors
- 5. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation PROBABLY NOT MISSING, BUT HARD TO DO
- 6. GAPS IN BIOMETRIC TESTING • There have been several papers on the contribution of individual error on performance – What causes these errors? • There are some papers that examine meta-data and the contribution of variables (age) and examines the training of algorithms
- 7. GAPS IN BIOMETRIC TESTING • Training – How do users get accustomed to devices – Can they remember how to use them – How do we provide good training to the users that has a consistent message
- 8. GAPS IN BIOMETRIC TESTING • Accessibility – How many people know people (!) who have problems with interacting with a biometric systems – How do we deal with accessibility and usability issues • Hearing and sight issues
- 9. GAPS IN BIOMETRIC TESTING • Human Factors – Testing and evaluating biometric systems by looking at how the users interact with the system • Are performance results different in an operational environment than collect in a lab? • Are these performance results due to the environment?
- 10. GAPS IN BIOMETRIC TESTING • It the error always subject centric? – The role of the device? – The role of the operator?
- 11. BIOMETRICS LAB Biometric Standards, Performance and Assurance Laboratory Department of Technology, Leadership and Innovation FILLING IN THOSE GAPS
- 12. WORK IN PROGRESS • Interaction methodologies such as HBSI have been addressing issues such as interaction errors from the subject perspective • Developed a framework for the establishment of metrics • Continual work on defining those metrics • Evaluation methodology
- 13. INTERACTION
- 14. AND MY TIME IS UP… • An additional presentation on the Evolution of the HBSI model is tomorrow.