Distinction of Wet Road Surface Condition at Night Using Texture Features

Abstract

The necessity of distinguishing the road surface condition at night time is increasing because most of the previously proposed methods correspond only to daytime. In this paper, we propose a method of distinguishing road surface condition using only video information acquired from a visible surveillance video camera. The feature of this method is that it simply uses automobile headlights as the light source. Thus it becomes possible to distinguish between road surface conditions, such as dry and wet, with high accuracy using this method. C⃝ 2014 Wiley Periodicals, Inc. Electron Comm Jpn, 97(6): 51-57, 2014; Published online in Wiley Online Library (wileyonlinelibrary.com).

Clustering learning model of CCTV image pattern for producing road hazard meteorological information

“…Previous research on road hazard weather information has emphasized the importance of identifying and providing dangerous roads to vehicle drivers in advance to prevent traffic accidents [23,24,25]. In order to collect road weather information, there have been previous studies [26,27,28,29] that produce road weather information using roadside CCTV images instead of costly fixed RWIS. However, previous studies have focused only on state information of road weather such as snow, fog, and rain on the road.…”