Assessment of image sensor performance with statistical perception performance analysis

The performance of perceptive systems depends on a large number of factors. The practical problem during development is, that this dependency is very often not explicitly known. In this contribution we address this problem and present an approach to evaluate perception performance, as a function of e.g. quality of the sensor data. The approach is to use standardized quality metrics for imaging sensors, and to relate them to the observed performance of the environment perception. During our experiments, several imaging setups were analyzed. The output of each setup is processed offline to track down performance differences with respect to the quality of sensor data. We show how and to what extend the measurement of the Modulation Transfer Function (MTF) using standardized tests can be applied to evaluate the performance of imaging systems. The influence of the MTF on the signal-to-noise ratio can be used to evaluate the performance on a recognition task. We assess the measured performance by processing the data of different, simultaneously recorded imaging setups for the task of lane recognition