用聚类算法提取基于彩色特征的语义物体

Extracting Semantic Object Based on Color Feature Using Clustering Algorithm

该文提出一种用聚类算法提取基于彩色特征的语义物体的方法。首先把RGB空间转化为L*a*b*空间,然后用最近邻算法进行聚类,把图象中象素依次聚类到各个颜色区域中,最后,根据彩色信息提取出语义物体,实验表明该方法具有实用性,并且对图象语义信息的研究有很大的帮助。

In this paper we present an approach to extract semantic object based on color feature using clustering analysis.Firstly,we translate RGB space into space.Secondly,we use the nearest neighbor rule algorithm to solve clustering problem.At the end,we extract semantic object in terms of color information.Experimental results show that the color clustering gives superior results in increases in cluster compactness.