期刊论文

An Image Retrieval Algorithm Based on Multi-feature Fusion

中文

电讯技术

1001-893X

2017

57

9

1023-1029

10.3969/j.issn.1001-893x.2017.09.008

61772561:国家自然科学基金 61602528:国家自然科学基金 61602529:国家自然科学基金

本校为第一机构

针对单一特征不能很好地表述图像的问题, 提出了一种融合多特征的图像检索算法.首先, 提取查询图像和图像库中样本图像的GIST （ Gener alized S earch Tree ）特征, 用欧氏距离衡量图像间的 GIST相似度值, 根据查询图像的GIST 特征在图像库中进行检索, 将结果按相似度进行排序; 然后, 提取查询图像和返回结果中前k 幅图像的尺度不变特征变换（ SIFT ）特征, 使用BBF （Best Bin First） 算法进行特征匹配; 最后, 通过特征点匹配点对数排序并返回检索结果.实验在改进的Corel1000数 据集上进行, 与传统的单特征图像检索算法对比, 提出的图像检索算法不仅提高了检索准确率, 而且 获得了较好的检索...

In order to solve the problem that the single feature cannot represent an image completely,an im-age retrieval algorithm based on multi-feature fusion is proposed. First,the generalized search tree( GIST) features of the query image and all the images in the image library are extracted. The similarity of two ima-ges is measured by the Euclidean distance. The image library is retrieved by the GIST feature of the query image,and the results are arranged by sorting the similarity value. Second,the scale invariant feature trans-form( SIFT) features of the query image are extracted as well as the k...