DefinePK

Abstract

In recent years, the use of surveillance cameras is increasingly recommended and they have been installed in many places. Snowy conditions at the time of an accident were associated with the problem that cars and accident circumstances become difficult to discern in images shot during snowfall. Previous techniques proposed methods for elimination of noise caused by snow using image shift or dedicated filters for the elimination of snowfall in video. However, these are associated with issues such as inability to cope with heavy snowfall or moving objects fading from view or being hard to discern. The present study proposes a method for snowfall noise elimination by extracting moving objects using the travel and the size of the moving object region between continuous frames, shaping a moving object using a convex hull algorithm, and compositing images while using the difference mask image excluding the moving object area. By distinguishing between falling snow and other moving objects, we can prevent objects other than snowfall becoming invisible. In addition, the convex hull can prevent to get out of shape of moving objects other than snowfall. In order to confirm the effectiveness of the proposed method by experiments, we used a video in which cars actually run in a snowfall environment. As shown in the experimental results, it can be confirmed that the snow grains are removed and the shapes of the cars in the image are kept well.