Additional Traffic Sign Detection -- A Comparative Study

Automated driving is a long term goal that currently generates a lot of interest and effort in the scientific community and the industry. A crucial step towards it is being able to read traffic signs along the roads. Unfortunately, state-of-the-art traffic sign detectors currently ignore the existence of additional traffic signs. Yet being able to recognize these is a requirement for the task of automated driving and automated map data updates, because they further determine the meaning or validity of main signs. In this paper we aim at the detection of these additional signs, a first step towards their recognition. We will have a careful look at suitable evaluation measures and then use these to compare our proposed MSER-based approach to a selection of five differing types of detectors from the literature. We achieved a substantial improvement of the state of the art with 90% successful detections with full sign content detection on a challenging dataset, while significantly reducing the number of false positives. We will present our database, which contains high-resolution images of German traffic signs suitable for optical character recognition. We rely on hand-labelled main signs to emphasize the focus on additional sign detection. Our results were confirmed on a validation set containing European additional signs.