Article
Towards the generation of synthetic images of palm vein patterns: a review
Autor
Salazar-Jurado, Edwin
Hernández-García, Ruber
Vilches-Ponce, Karina
Barrientos, Ricardo
Mora, Marco
Gaurav, Jaswal
Institución
Resumen
With the recent success of computer vision and deep learning, remarkable progress has been achieved on
automatic personal recognition using vein biometrics. However, collecting large-scale real-world training
data for palm vein recognition has turned out to be challenging, mainly due to the noise and irregular
variations included at the time of acquisition. Meanwhile, existing palm vein recognition datasets are usually
collected under near-infrared light, lacking detailed annotations on attributes (e.g., pose), so the influences
of different attributes on vein recognition have been poorly investigated. Therefore, this paper examines the
suitability of synthetic vein images generated to compensate for the urgent lack of publicly available large-
scale datasets. Firstly, we present an overview of recent research progress of palm vein recognition, from
the basic background knowledge to vein anatomical structure, data acquisition, public database, and quality
assessment procedures. Then, we focus on the state-of-the-art methods that have allowed the generation of
vascular structures for biometric purposes and the modeling of biological networks with their respective
application domains. In addition, we review the existing research on the generation of style transfer and
biological nature-based synthetic palm vein images algorithms. Afterward, we formalize a general flowchart
for the creation of a synthetic database comparing real palm vein images and generated synthetic samples to
obtain some understanding into the development of the realistic vein imaging system. Ultimately, we conclude
by discussing the challenges, insights, and future perspectives in generating synthetic palm vein images for
further works.