A Survey on Scalable Image Indexing and Searching

被引:0
|
作者
Suchitra, S. [1 ]
Chitrakala, S. [1 ]
机构
[1] Anna Univ, Madras 600025, Tamil Nadu, India
关键词
Content-based image retrieval (CBIR); Indexing and Searching; RELEVANCE FEEDBACK; RETRIEVAL; TREES;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Content-based image retrieval (CBIR) has been one of the most research areas in the field of computer vision over the last ten years. CBIR is a problem that is getting more and more attention. Many of the research works had been undertaken in the past decade to design efficient image retrieval techniques from the image or multimedia databases. Although large number of indexing and retrieval techniques has been developed, there is still no universally accepted feature extraction, indexing and retrieval technique available. The amount of image data that has to be stored, managed, searched, and retrieved grows continuously on many fields of industry and research. One key challenge in CBIR is to develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems. In this survey presents a highlight on the role of image indexing. It also point out scope and challenges in designing of image retrieval systems.
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页数:5
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