TRAFFIC LIGHTS DETECTION IN ADVERSE CONDITIONS USING COLOR, SYMMETRY AND SPATIOTEMPORAL INFORMATION

Abstract

This paper proposes the use of a monocular video camera for traffic lights detection, in a variety of conditions, including adverse weather and illumination. The system incorporates a color pre-processing module to enhance the discrimination of red and green regions in the image and handle the “blooming effect” that is often observed in such scenes. The fast radial symmetry transform is utilized for the detection of traffic light candidates and finally false positive results are minimized using spatiotemporal persistency verification. The system is qualitatively assessed in various conditions, including driving in the rain, at night and in city roads with dense traffic, as well as their synergy. It is also quantitatively assessed on a publicly available manually annotated database, scoring high detection rates.