With the development of autonomous driving and driving assistance, cameras are more and more significant in the Automotive industry. Whereas the evaluation of image quality for consumer cameras such as smartphone cameras has been well defined for years, the definition of a good image quality for an ADAS camera, fully dedicated to computer vision, is still under debate. It seems obvious that the KPIs for camera evaluation need to be redefined in the light of this new scope. In 2022, DXOMARK has launched an ambitious research program (in partnership with a French institute specialized in detection algorithm) to evaluate various image quality evaluation metrics. The aim of the research program is to correlate the result of three different metrics – Contrast Transfer Accuracy (CTA), Contrast Signal to Noise Ratio (CSNR) and Frequency of Correct Resolution (FRC) – with the success of a license plate reading algorithm based on a neural network. In this talk, we are going to introduce the protocol that we have designed for this purpose and the preliminary conclusions that we draw on the three metrics.