Road segmentation and obstacle detection by a fast watershed transformation

Abstract

This paper presents the work, performed at CMM as part of the European PROMETHEUS project, concerning road/lane segmentation and obstacle detection in a dynamic scene. Road/lane segmentation is used to select ROI where obstacle detection algorithms are applied. This segmentation is made up of a temporal filter, an edge detector and a watershed transformation. It produces a marker of the current traffic lane. This marker is then used for calculating a road model which is continuously updated. The obstacle detection uses various criteria: existence of a darker region marking a vehicle, size and contrast of obstacles and symmetry. These two processes use the watershed transformation which is usually the slowest part of the segmentation. To speed it up, a very efficient enhancement of the algorithm, based on anamorphosis, is presented.