一种融合聚类与区域生长的彩色图像分割方法

论文提出了一种将聚类和区域生长有机融合的彩色图像分割方法。为了捕获图像的纹理特征,首先将图像划分成16×16子块,然后在块中按照视觉一致性准则进行颜色聚类,对于聚类后的子块,提取其颜色与纹理特征,然后采用符合人类视觉特征的生长规则,进行基于子块的区域生长。该方法充分利用了聚类算法和区域生长算法的各自优点,并符合人类视觉特征的分割策略。利用提出的算法对多幅自然图像进行了分割实验,实验结果证明了算法的有效性。

A Color Image Segmentation Method by Fusion of Clustering and Region Growing

This paper presents a color image segmentation method by combination of clustering and region growing techniques.In order to capture the texture feature of color image,the original image is first partitioned into 16×16 sub-blocks which are not overlapped,and then the sub-blocks are segmented by color clustering algorithm based on perceptual uniformity.Color and texture features are extracted from the segmented sub-blocks,and a block growing algorithm is employed to achieve segmentation for the whole image based on growing rules determined in term of human vision characteristics.The proposed method combines the advantages of clustering and region growing approaches,which is in accord with the human segmentation strategy.The new algorithm is applied to segment a number of natural images and its effectiveness and efficiency is confirmed by experimental results.