LAUSR

Characteristics of the tire footprint are major indicators of tire performance and provide relevant information that can be used to improve the tire design process. However, the accurate segmentation of the tire footprint requires prior training and can be a highly man-hour consuming task. In order to overcome such drawbacks, scientists have made multiple efforts to design methods for segmenting the tire footprint automatically but it is still an open problem. In this paper, we propose a novel methodology to estimate the tire footprint under dynamic conditions and conduct an extensive subjective assessment of its quality. For this aim, we designed a subjective evaluation procedure based on the ITU-R BT.500–13 recommendation. In addition, we include a quantitative comparison of several tire contact patch segmentation methods using ray feature error and Dice index. The results of our methodology have been evaluated by expert tire engineers and will allow us to improve the tire manufacturing process.