摘要
在基于内容的图像检索中,图像特征的维数往往随着图像特征描述的详尽而剧烈的增加,在建立图像库时高维特征的存储空间度以及度量图像之间相似性的运算复杂度都将非常高.采取一个颜色均匀性谓词对图像进行多层分解来提取图像的颜色特征,在此基础上与LLE算法相结合对图像的高维特征进行降维.实验表明,该相关算法具有较好的性能.
In content based image retrieval, the dimension of an feature vector will increase seriously when more details of the image are given. The spratial complexity of high eigenvector＇s storage and operation of computing their similarity will be much higher. An image is decomposed by a color homogeneity predicate to get the feature of color, and LLE is applied to the dimension reduction to reduce both the spatial and operation complexity. Experimental results shown that LLE united with this way of abstract the feature of an image have better results.
出处
《高师理科学刊》
2009年第3期26-29,共4页
Journal of Science of Teachers＇College and University
关键词
基于内容的检索
图像分解
LLE
降维
content-based retrieval
decomposing of an image
LLE
dimension reduction
