Robust Morph-Detection at Automated Border Control Gate using Deep Decomposed 3D Shape and Diffuse Reflectance

TL;DR

This paper introduces a robust morph detection method for Automated Border Control gates that uses differential analysis of 3D shape and reflectance features, significantly improving attack detection accuracy.

Contribution

The paper presents a novel morph detection algorithm based on decomposing images into diffuse and normal map components, with a fusion scheme for enhanced accuracy in ABC scenarios.

Findings

Outperforms existing state-of-the-art methods in ABC gate scenarios

Creates a new morph attack database with 588 images

Achieves high detection accuracy with feature decomposition and score fusion

Abstract

Face recognition is widely employed in Automated Border Control (ABC) gates, which verify the face image on passport or electronic Machine Readable Travel Document (eMTRD) against the captured image to confirm the identity of the passport holder. In this paper, we present a robust morph detection algorithm that is based on differential morph detection. The proposed method decomposes the bona fide image captured from the ABC gate and the digital face image extracted from the eMRTD into the diffuse reconstructed image and a quantized normal map. The extracted features are further used to learn a linear classifier (SVM) to detect a morphing attack based on the assessment of differences between the bona fide image from the ABC gate and the digital face image extracted from the passport. Owing to the availability of multiple cameras within an ABC gate, we extend the proposed method to fuse the classification scores to generate the final decision on morph-attack-detection. To validate our proposed algorithm, we create a morph attack database with overall 588 images, where bona fide are captured in an indoor lighting environment with a Canon DSLR Camera with one sample per subject and correspondingly images from ABC gates. We benchmark our proposed method with the existing state-of-the-art and can state that the new approach significantly outperforms previous approaches in the ABC gate scenario.