BioGaze: a Framework for Evaluating the Photographic Requirements of the ISO/IEC 39794-5 Standard

Facial recognition is a key biometric technology, especially for using electronic documents in real-world applications. The accuracy of this recognition technology strictly depends on the image quality, i.e. the face appearance in the image included in the document. Then, adherence to ISO/ICAO standards, which contain guidelines to standardize the image quality in official documents, is of paramount importance. However, ensuring compliance is challenging due to high subject variability. Furthermore, controls are often executed manually, making them subjective and time-consuming. Therefore, in this work, we introduce BioGaze, an automated framework for ISO/ICAO compliance verification that combines classical computer vision and deep learning algorithms to perform the checks contained in the latest standard version. The framework is tested on a synthetic dataset, achieving state-of-the-art performance across multiple ISO/ICAO requirements, surpassing public algorithms and commercial SDKs. BioGaze is publicly available to advance automated compliance verification and support standardization efforts¹.¹https://github.com/MI-BioLab/BioGaze