Advertisement Detection, Segmentation, and Classification for Newspaper Images and Website Snapshots

Wei Ta Chu, Han Yuan Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Advertisement plays an important role in the human society. Advertisement studies are related to many important issues in economics, social science, and marketing. In this paper, we propose a system to detect, segment, and classify advertisements from newspaper images and website snapshots, in order to facilitate advertisement studies. First, we detect advertisement candidates based on a connected components method. We then design rule-based filters and learning-based filters to remove non-advertisement candidates. From the remained advertisement candidates, we extract visual features and construct classifiers to classify them into predefined advertisement categories. Based on the advertisement categories published over years, we uncover several interesting statistics derived from newspaper front pages and website snapshots.

Original languageEnglish
Title of host publicationProceedings - 2016 International Computer Symposium, ICS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages396-401
Number of pages6
ISBN (Electronic)9781509034383
DOIs
Publication statusPublished - 2017 Feb 16
Event2016 International Computer Symposium, ICS 2016 - Chiayi, Taiwan
Duration: 2016 Dec 152016 Dec 17

Publication series

NameProceedings - 2016 International Computer Symposium, ICS 2016

Other

Other2016 International Computer Symposium, ICS 2016
CountryTaiwan
CityChiayi
Period16-12-1516-12-17

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Science Applications

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