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中文摘要：
以粗糙集理论为基础分析彩色图像分割概念，研究已有的彩色图像分割方法，将粗糙集的上、下近似集理论与云模型理论相结合，提出基于粗糙集和云模型的彩色图像分割方法．该方法在HSV颜色空间对彩色图像进行非均匀量化，并寻找量化后图像的基本直方图和Histon直方图，根据粗糙集理论中粗糙度概念得到图像的粗糙直方图，最后通过云模型的”3En规则”对图像进行前景／背景分割．通过三组实验验证了该方法的正确性，并与K均值算法、A—IFSHRI算法进行比较，实验结果表明了该方法对彩色图像分割的有效性．
英文摘要：
Through analyzing the concept of color image segmentation, studying the existing image segmentation methods and combi- ning the upper and the lower approximation of rough set theory with cloud model, which are all based on rough set theory, the method of color image segmentation based on rough set and cloud model is proposed. The method quantifies color image in HSV color space, and looks for the histogram and histon-histogram of the quantized image, according to the roughness concept in rough set theory, rough-histogram of the image is proposed, the finally, foreground of image is segmented from background by the ＂3En Rules＂ of the cloud model. Three experiments verify the correctness of the method, furthermore, experimental results show the validity of the pro-posed method comparing with K-means and A-IFS HRI algorithm.
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