摘要
分析了基于兴趣点的图像检索方法的缺点,提出了一种基于小波突出点的图像检索新方法。该方法在小波域提取突出点,这些突出点既表示了全局变化也表示了局部变化;然后以小波突出点为线索,设计了基于小波突出点的环形颜色直方图,既利用了小波突出点的局部特征,又考虑了小波突出点的空间分布结构;用图像间的环形颜色直方图距离来度量图像间的相似性。该检索算法不但保证了对图像旋转、平移鲁棒性,而且克服了传统直方图没有空间位置的缺陷。实验结果表明,该方法对图像检索是有效的。
Having analyzed the drawbacks of image retrieval based on interest points, a novel image retrieval algorithm is proposed using wavelet-based salient points in this paper. The algorithm extracts the salient points in wavelet domain, these salient points not only represent global variations as well as local variations; then the salient points are regarded as clues, and annular color histogram is designed, which takes not only the local color feature into consideration, but also the space distribution information of the salient points; the similarities are measured by the distance of annular color histograms. With robustness to rotation and translation, the algorithm avoids shortcoming of losing the location information in the traditional color histogram. Experimental results show that this algorithm is efficient for image retrieval.
出处
《计算机科学》
CSCD
北大核心
2006年第5期250-252,289,共4页
Computer Science
基金
十五国防科技(电子)预研项目(413160501)
关键词
图像检索
小波突出点
环形颜色直方图
Image retrieval, Wavelet salient points, Annular color histogram
