Image Shadow Detection and Classification Based on Rough Sets

The theory of the rough sets is a new mathematics tool which used to process fuzzy and indetermination problem, this paper put 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 gets 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