Web-based Beowulf-Class parallel computing on image database indexing and retrieval system

被引：2
|
作者：
Cheung, CH [1 ]
Po, LM [1 ]
Wong, KM [1 ]
机构：
[1] City Univ Hong Kong, Dept Elect Engn, CityU Image Proc Lab, Kowloon, Hong Kong, Peoples R China
来源：
PROCEEDINGS OF 2001 INTERNATIONAL SYMPOSIUM ON INTELLIGENT MULTIMEDIA, VIDEO AND SPEECH PROCESSING | 2001年
关键词：
content-based image retrieval; parallel computing; Image database indexing and retrieval system; Beowulf;
D O I：
10.1109/ISIMP.2001.925432
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Content-Based Image Retrieval (CBIR) techniques will be served as the next generation of search engine. However, even with a suitable retrieval method, real-time image retrieval from a large image database still requires extremely high computational power. In this paper, a web-based image database indexing and retrieval system is described. It uses fast CBIR with Beowulf-Class parallel computing engine (Super Abacus) to efficiently and effectively shorten the retrieval time. The content-based image retrieval with several parallel algorithms for images query from different color spaces and the compressed-domain of images are developed to achieve higher efficiency. Besides, the text-based query is also supported for images query using the conventional annotation approach.
引用
收藏
页码：457 / 460
页数：4
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