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Image Shadow Detection and Classification Based on Rough Sets
基于粗糙集阴影区域的检测与分类

Keywords: Rough set,Shadow classification,Shadow detection,Shadow edge,Edge gradient,Biggest error of neighborhood
粗糙集
,阴影分类,图像分割,阴影边缘,边缘梯度,最大邻域差

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Abstract:

The theory of the Rough sets is a new mathematics tool which is used to process fuzzy and indetermination problem,this paper puts forward a new method of the shadow edge classification based on Rough sets,which according to the theories of the Rough sets and the condition attribute of the gradient,the biggest error of neighborhood and the noise.The method divides a picture into the different several sub-pictures,then respectively process the sub-picture and get the shadow edge points.Then these edge points are thinned and followed and those false edge points are deleted.Then a imaginable shadow district is formed according to the shadow edge.The method statistics the gray histogram of these districts and get a gray zone of the shadow district.Then the shadow district is got and the shadow can be classified according to some characteristics such as the gray and the shape and the area of zone etc.It draws the conclusion by analyzing the result:the detecting accuracy and visual effect are improved by comparing the edge detection method based on rough set with normal methods.

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