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一种基于模糊聚类的快速二值化方法
A FUZZY-CLUSTERING-BASED QUICK BIVALUED APPROACH
【摘要】 通过确定阈值实现图像的二值化分割是一种重要且实用的图像分割技术.本文提出了一种基于模糊聚类的二值化方法.这种方法将模糊C-均值算法加以推广(GFCM)后,应用于图像的二值化分割.通过与Otsu阈值法的分割结果比较后表明,该方法的分割效果好,分割耗时少且适用性强.
【Abstract】 It is an important and practical technique for image segmentation to select a threshold forbinarization of images. In the paper, an approach of fuzzy-clustering-based binarization is proposed,which is a generalization of fuzzy C-means(FCM) algorithm and is used in bivalued segmentation ofimages. The comparison of segmentation results with Otsu’s thresholding method show that theapproach has better segmentation effect, less segmentation time-consuming and more widespreadadaptability.
【关键词】 图像分割;
图像二值化;
模糊聚类;
模糊C-均值算法;
【Key words】 Image segmentation; image binary; fuzzy clustering; fuzzy C-means algorithm;
【Key words】 Image segmentation; image binary; fuzzy clustering; fuzzy C-means algorithm;
- 【文献出处】 计算机学报 ,CHINESE JOURNAL OF COMPUTERS , 编辑部邮箱 ,1998年S1期
- 【分类号】TP391.4
- 【被引频次】55
- 【下载频次】393