摘要
提出了一种基于小波和相对矩的形状特征提取与检索方法。首先,对亮度图像进行小波多尺度边缘检测,得到多尺度边界图像;然后,计算每一尺度的7个不变矩,再转化为10个相对矩,所有尺度上的相对矩组成图像的特征向量;最后,对特征向量进行高斯归一化,用欧氏距离度量图像间的相似度,构建了一个基于形状特征的图像检索系统。实验结果表明,该方法具有明显的优越性和通用性。
This paper presents a shape feature extraction and image retrieval method based on wavelet and relative moments.Firstly, it processes the luminance images with wavelet edge detection to get multi-scale edge images, then calculates the seven invariant moments of every scale, and translates to ten relative moments, which a group of multi-scale relative moments vectors in feature space characterize each image. Finally, the Euclidean distance between two images' normalized moment vectors gives the measure of similarity, and constructs a shape-based image retrieval system. Experimental results verify the superiority and currency of this method.
出处
《计算机工程》
CAS
CSCD
北大核心
2004年第20期146-147,共2页
Computer Engineering
基金
广西科学基金资助项目(桂科自0007012
桂科基0342046)
关键词
基于形状的图像检索
多尺度边缘检测
不变矩
相对矩
Shape-based image retrieval
Multi-scale edge detection
Invariant moments
Relative moments
