Visual Keyword Image Retrieval Based on Synergetic Neural Network for Web-Based Image Search

被引：0
|
作者：
Tong Zhao
Lilian H. Tang
Horace H. S. Ip
Feihu Qi
机构：
[1] Shanghai Jiao Tong University,Department of Computer Science and Engineering
[2] University of Surrey,School of Electronics, Computing and Mathematics
[3] City University of Hong Kong,Centre for Innovative Applications of Internet and Multimedia Technologies, (AIM tech Centre)
[4] Shanghai Jiao Tong University,Department of Computer Science and Engineering
来源：
Real-Time Systems | 2001年 / 21卷
关键词：
Synergetic neural network; Trademark image retrieval; Affine-invariant feature; Visual keywords; web-based multimedia search;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Feature extraction and similarity measure are two basickey issues in image retrieval. Combining the advantages of SNNin image recognition and selective attention for image retrieval,a novel visual keywords-driven image retrieval approach basedon these properties has been proposed. By using a predefinedset of visual keywords as prototype patterns stored with theSNN and then measuring the degree of similiarity of the storedimages to the visual keywords, we show that such a visual keyworddriven SNN can provide the framework for image indexing or retrievalwhich is scalable, robust and efficient for web-based search.
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页码：127 / 142
页数：15
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