Learning to remove reflections for text images

Ce Wang, Renjie Wan, Feng Gao, Boxin Shi, Ling Yu Duan*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

5 Citations (Scopus)

Abstract

Text images taken behind a piece of glass in the wild are largely contaminated by reflections. Directly applying existing reflection removal methods on text images with reflections cannot recover clear and correct text contents due to the ignorance of special characteristics of texts. This paper proposes a stacked framework to solve the text image reflection removal problem by specifically considering the regional properties of reflection and embedding the specific text priors into the estimation process in a unified manner. Experiment results on a newly collected dataset demonstrate that the proposed method outperforms state-of-the-art methods in recovering visually pleasant reflection-free images and recognizable text features.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Multimedia and Expo, ICME 2019
PublisherIEEE
Pages1276-1281
Number of pages6
ISBN (Electronic)9781538695524
ISBN (Print)9781538695531
DOIs
Publication statusPublished - 8 Jul 2019
Externally publishedYes
Event2019 IEEE International Conference on Multimedia and Expo, ICME 2019 - Shanghai, China
Duration: 8 Jul 201912 Jul 2019

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
Volume2019-July
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Conference

Conference2019 IEEE International Conference on Multimedia and Expo, ICME 2019
Country/TerritoryChina
CityShanghai
Period8/07/1912/07/19

User-Defined Keywords

  • GAN
  • Reflection removal
  • Text image
  • Text recognition

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