基于颜色量化和模糊C-均值聚类的彩色图像分割
首发时间:2010-03-12
摘要:提出了一种基于颜色量化和模糊C-均值聚类的的彩色图像分割方法。将颜色从RGB空间转化为HSV空间,在HSV空间的基础上将颜色量化,在量化颜色的基础上提取主颜色,以主颜色的个数和值分别作为聚类个数和聚类中心。然后采用自适应的模糊C-均值聚类算法将图像进行分割。对多幅自然彩色图像进行分割实验,实验结果证明了算法的有效性。
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Color Image Segmentation Based on Color Quantization and Fuzzy C-means Clustering
Abstract:A method of image segmentation based on color quantization and fuzzy c-means clustering is presented in this paper. Color space is converted from RGB to HSV, and then is quantized. Based on quantized HSV color space, the dominant colors and the number of dominant colors are chosen as the initializing clustering centers and the initializing clustering number. Finally, an adaptive fuzzy C-mean clustering is used to segment color images. The new method is applied to segment many natural color images, and experimental results show the effectiveness and efficiency of the method.
Keywords: image segmentation color quantization dominant color fuzzy c-means clustering
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