Survey on content-based image retrieval

被引：0
|
作者：
Liu Huailiang [1 ]
机构：
[1] Xidian Univ, Sch Econ & Management, Xian 710071, Peoples R China
来源：
Wavelet Active Media Technology and Information Processing, Vol 1 and 2 | 2006年
关键词：
CBIR; feature extraction; evaluation; prototype;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Some key techniques for CBIR, including visual features description and extraction, similarity/distance measures, system performance evaluation, is pictured. The principle of CBIR is to make a similarity comparison and distance calculation between features of query image and images in database. Color, texture, shape, and spatial information etc., general visual features most widely used in CBIR are discussed. Various ways to calculate the similarity distances between visual features are presented. Furthermore, QBIC is introduced as a prototype system.
引用
收藏
页码：930 / 935
页数：6
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