Biometric enhancements: Template aging error score analysis

Identity capabilities are being modernized through biometric technology and systems. With maturing biometrics in full, rapid development, a higher accuracy of identity verification is required. Improvements to the security of biometric verification systems is provided through higher accuracy; ultimately reducing fraud, theft, and loss of resources from unauthorized personnel. With trivial biometric systems, a higher acceptance threshold to obtain higher accuracy rates increased false rejection rates and user unacceptability. However, maintaining the higher accuracy rate enhances the security of the system. Through the methods presented in this paper, higher accuracy rates are obtained without lowering the acceptance threshold, therefore improving the security level, false rejection rates, and user acceptability. An area of biometrics with a paucity of research is template aging, specifically in regards to facial aging. This paper presents methods of modeling and predicting facial template aging based on matching score analysis. A novel foundational framework for facial template aging is presented and provides a methodological framework. The groundwork discusses new techniques used in the template aging framework, to include the ldquoerror score matrixrdquo and ldquodecay error estimaterdquo concepts. The matching scores are calculated using commercially available facial matching algorithms/SDKs against publicly available facial databases. Improved performance error rates while maintaining or improving upon the overall matching and/or rejection levels is accomplished with the new framework. Using such scores, prediction of a timeframe if or when an individual needs to be re-enrolled with a new template is feasible.