An efficient algorithm for periodic halftone identification

Shintami C. Hidayati, Che Hao Hsu, Shih Wei Sun, Wen-Huang Cheng, Kai Lung Hua

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

When periodic halftoned documents (e.g., books, newspapers, and magazines) are scanned for image reproduction, moiré patterns occur. In order to avoid these moiré artifacts, it is necessary to detect the periodic halftone. This paper provides a fast Fourier transform based method to classify periodic halftoned documents. Experimental results show that the overall accuracy of this method is 97% on a large data set which contains many difficult-to-classify images. Misclassified documents tend to be extremely difficult to classify, in that they contain very small periodic halftone regions. An existing method, by comparison, has accuracy of only 70%.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479970797
DOIs
StatePublished - 28 Jul 2015
Event2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015 - Turin, Italy
Duration: 29 Jun 20153 Jul 2015

Publication series

Name2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015

Conference

Conference2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015
CountryItaly
CityTurin
Period29/06/153/07/15

Keywords

  • Periodic halftone noise
  • fast Fourier transform
  • moiré patterns

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