Windscreen Optical Quality for AI Algorithms: Refractive Power and MTF
  not Sufficient
Dominik Werner Wolf Markus Ulrich Alexander Braun
Windscreen optical quality is an important aspect of any advanced driver
assistance system, and also for future autonomous driving, as today at least
some cameras of the sensor suite are situated behind the windscreen. Automotive
mass production processes require measurement systems that characterize the
optical quality of the windscreens in a meaningful way, which for modern
perception stacks implies meaningful for artificial intelligence (AI)
algorithms. The measured optical quality needs to be linked to the performance
of these algorithms, such that performance limits - and thus production
tolerance limits - can be defined. In this article we demonstrate that the main
metric established in the industry - refractive power - is fundamentally not
capable of capturing relevant optical properties of windscreens. Further, as
the industry is moving towards the modulation transfer function (MTF) as an
alternative, we mathematically show that this metric cannot be used on
windscreens alone, but that the windscreen forms a novel optical system
together with the optics of the camera system. Hence, the required goal of a
qualification system that is installed at the windscreen supplier and
independently measures the optical quality cannot be achieved using MTF. We
propose a novel concept to determine the optical quality of windscreens and to
use simulation to link this optical quality to the performance of AI
algorithms, which can hopefully lead to novel inspection systems.