计算机技术与发展2016，Vol.26Issue(12)：17-21,5.DOI:10.3969/j.issn.1673-629X.2016.12.004
基于自适应希尔伯特扫描和词袋的图像检索
Image Retrieval Based on Adaptive Hilbert Scan and Bag of Features
摘要
Abstract
One fundamental problem in large scale image retrieval with the bag-of-features is its lack of spatial information. An approach called adaptive Hilbert-scan depended on distribution of features in an image is proposed. This method computes weight of each Hilbert-scan at increasingly fine resolutions by analysis of feature distribution in the image,which is able to assign a suitable scanning path for each image. Hilbert-scan based tree structure is studied and its advantage ad disadvantage is analyzed. The method adds the spatial infor-mation of local features into each node of tree,furthermore a novel adaptive Hilbert-scan strategy with multi-level is designed,which is built on the distribution of features in image. Owing to merits of this method,spatial information of features will be preserved more pre-cisely in Hilbert-scan based tree structures. Extensive experiments on Caltech-256 show the effectiveness of the method.关键词
希尔伯特扫描/图像检索/词袋/特征表示Key words
Hilbert-scan/image retrieval/bag-of-features/feature representation分类
信息技术与安全科学引用本文复制引用
徐墨,刘福岩,余梦婷..基于自适应希尔伯特扫描和词袋的图像检索[J].计算机技术与发展,2016,26(12):17-21,5.基金项目
国家自然科学基金面上项目(61471232) （61471232）
