FaceQvec: Vector Quality Assessment for Face Biometrics based on ISO Compliance

TL;DR

FaceQvec is a software tool that automates the assessment of facial image quality based on ISO standards, improving face recognition accuracy by identifying and addressing quality issues.

Contribution

This paper introduces FaceQvec, a novel automated system for evaluating facial image quality according to ISO/IEC 19794-5 standards, with validation on realistic datasets.

Findings

High accuracy of individual quality tests

Effective threshold adjustment based on development data

Validated performance on unseen face images

Abstract

In this paper we develop FaceQvec, a software component for estimating the conformity of facial images with each of the points contemplated in the ISO/IEC 19794-5, a quality standard that defines general quality guidelines for face images that would make them acceptable or unacceptable for use in official documents such as passports or ID cards. This type of tool for quality assessment can help to improve the accuracy of face recognition, as well as to identify which factors are affecting the quality of a given face image and to take actions to eliminate or reduce those factors, e.g., with postprocessing techniques or re-acquisition of the image. FaceQvec consists of the automation of 25 individual tests related to different points contemplated in the aforementioned standard, as well as other characteristics of the images that have been considered to be related to facial quality. We first include the results of the quality tests evaluated on a development dataset captured under realistic conditions. We used those results to adjust the decision threshold of each test. Then we checked again their accuracy on a evaluation database that contains new face images not seen during development. The evaluation results demonstrate the accuracy of the individual tests for checking compliance with ISO/IEC 19794-5. FaceQvec is available online (https://github.com/uam-biometrics/FaceQvec).