Abstract
Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.
Highlights
Face recognition systems provide the benefit of collecting a large amount of biometric information in a relatively easy and cost-effective manner, because they do not require subjects to bring any part of their body in contact with the recognition device intentionally, which results in fewer repercussions and less inconvenience when collecting the biometric information
The performance evaluation model (PEM) is designed to be compatible with related international standards, and contributes to the consistency and enhanced reliability of the performance evaluation tool that is developed with reference to the model
MET is a set of performance test measures such as fail-toenroll rate (FTER), fail-to-acquire rate (FTAR), and false nonmatch rate (FNMR), false match rate (FMT)
Summary
Formal Implementation of a Performance Evaluation Model for the Face Recognition System. Practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals’ facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. We propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. We performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process
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