摘要
提出了一种基于目标区域和相关反馈的图像检索方法,首先采用改进的K均值无监督分割方法将图像分割成区域,然后提取每个区域的颜色、位置、形状特征进行相似度计算;最后采用基于支持向量机(SVM)的相关反馈算法提高检索精度。实验结果表明,方法具有良好的检索性能。
A novel image retrieval method based on region and relevance feedback is proposed in this paper.At first,the proposed approach employs a improved K-mean and fully unsupervised segmentation algorithm to divide images into regions,and low-level feature for the color,position,shape of each region are subsequently extracted and applied in similarity measurement.At last a relevance feedback mechanism,based on support vector machines is invoked to improve the retrieval performance.The experiment results show that the method can get better retrieval performance.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第16期171-173,共3页
Computer Engineering and Applications
关键词
图像检索
图像分割
相似度计算
相关反馈
支持向量机
image retrieval
image segmentation
similarity measure
Relevance feedback
support vector machines
