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Webpage segmentation for extracting images and their surrounding contextual information
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International Multimedia Conference archive
Proceedings of the seventeen ACM international conference on Multimedia table of contents
Beijing, China
SESSION: Short papers session 2: content analysis and HCM table of contents
Pages 649-652  
Year of Publication: 2009
ISBN:978-1-60558-608-3
Authors
Fariza Fauzi  Monash University, Bandar Sunway, Malaysia
Jer-Lang Hong  Monash University, Bandar Sunway, Malaysia
Mohammed Belkhatir  Monash University, Bandar Sunway, Malaysia
Sponsor
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
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ABSTRACT

Web images come in hand with valuable contextual information. Although this information has long been mined for various uses such as image annotation, clustering of images, inference of image semantic content, etc., insufficient attention has been given to address issues in mining this contextual information. In this paper, we propose a webpage segmentation algorithm targeting the extraction of web images and their contextual information based on their characteristics as they appear on webpages. We conducted a user study to obtain a human-labeled dataset to validate the effectiveness of our method and experiments demonstrated that our method can achieve better results compared to an existing segmentation algorithm.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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