Webpage segmentation for extracting images and their surrounding contextual information

  • Authors:
  • Fariza Fauzi;Jer-Lang Hong;Mohammed Belkhatir

  • Affiliations:
  • Monash University, Bandar Sunway, Malaysia;Monash University, Bandar Sunway, Malaysia;Monash University, Bandar Sunway, Malaysia

  • Venue:
  • MM '09 Proceedings of the 17th ACM international conference on Multimedia
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

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.