摘要
提出了一种自动确定聚类数目的K-均值聚类算法,并基于这种算法介绍了一种彩色图像区域分割方法。这种方法首先选择合适的彩色空间,抽取图像的像素点颜色、纹理及位置等特征,形成特征向量空间;然后,在此特征空间中,运用提出的方法进行聚类和图像区域分割;最后,抽取图像区域的特征。对提出的方法进行了详细的介绍,给出实验结果分析,并与相类似的方法进行了比较实验。实验结果表明,提出的图像区域分割方法具有分割速度快、效果好等特点,适合于基于图像区域检索系统,具有较强的实用价值。
A K-means alogorithm of oneself decideing the clustering number is proposed,and based on this alogorithm,a method of region-based image segmentation is introduced.For this method,a suitable color space is selected,the features of color,texture, and location are extracted,and the feature space is formed.Then,in this feature space,an image is clustering and separate into regions by proposed method.Finally,the features of regions are extracted.In this paper,the proposed method is detailedly introduced,and the experiment results and the comparision results with the similar approach are provided.Experiment results show the proposed method has the quickly segmentation speed and good sementation results,and it is fit for region-based image retrieval system and has the better applied values.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第16期163-167,共5页
Computer Engineering and Applications
基金
广东省自然科学基金(the Natural Science Foundation of Guangdong Province of China under Grant No.7300450)
关键词
自适应K-均值聚类
图像区域分割
图像区域特征
self-adaptive K-means clustering
region-based image segmentation
features of image regions
