Digital correlations for visual quality criteria of headlamp light patterns

This thesis deals with the evaluation of automotive headlamp light distributions in regard to the non-uniformity or inhomogeneity of the distributions. While human observers have no difficulties in locating strong inhomogeneities, it has shown to be quite challenging to develop a generalized and automatic evaluation of different types of inhomogeneities. Consequently, the approach is based on the idea that non-uniformities of light distributions can only be fully evaluated if the contrast processing mechanisms of the human visual system are partly simulated. This work proposes a model that offers a simplified and functional simulation of human contrast processing. The model is composed of three serially connected submodules. Its performance is evaluated by comparing the results of the model to data collected with a human observer study. Additionally psychophysical measurement data from literature is used for a thorough evaluation of the model.