In this paper, detection of a vehicle from a road image with fog is focused to detect an vehicle from a foggy image. Because of the fog in the image, a shape of an object is vague. Therefore an obstacle may occur on t...In this paper, detection of a vehicle from a road image with fog is focused to detect an vehicle from a foggy image. Because of the fog in the image, a shape of an object is vague. Therefore an obstacle may occur on the vehicle detection. Thus, features from a foggy road image are surveyed through experinmlts, and a histogram is caloalated with the bright value. The stretching method is then applied with the specific weight as the centre to detect a vehicle smoothly. If the high density area, from the view point of histogram, is applied with the stretching method, the definition of the image can be increased. On this fact, this paper proposed a method to divide the histogram and to determine applicable range of the stretching method. The improved results by the proposed methods are proved with the camparison tests between the proposed and previous methods.展开更多
基金supported by the MKE(The Ministry of Knowledge Economy),Koreathe ITRC(Information Technology Research Center)support program(NIPA-2010-(C1090-1021-0010))the Brain Korea 21 Project in 2010
文摘In this paper, detection of a vehicle from a road image with fog is focused to detect an vehicle from a foggy image. Because of the fog in the image, a shape of an object is vague. Therefore an obstacle may occur on the vehicle detection. Thus, features from a foggy road image are surveyed through experinmlts, and a histogram is caloalated with the bright value. The stretching method is then applied with the specific weight as the centre to detect a vehicle smoothly. If the high density area, from the view point of histogram, is applied with the stretching method, the definition of the image can be increased. On this fact, this paper proposed a method to divide the histogram and to determine applicable range of the stretching method. The improved results by the proposed methods are proved with the camparison tests between the proposed and previous methods.
