Detection and segmentation of antialiased text in screen images

Sivan Gleichman, Boaz Ophir, Amir Geva, Mattias Marder, Ella Barkan, Eli Packer

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

6 Scopus citations

Abstract

Various software applications deal with analyzing the textual content of screen captures. Interpreting these images as text poses several challenges, relative to images traditionally handled by optical character recognition (OCR) engines. One such challenge is caused by text antialiasing, a technique which blurs the edges of characters, to reduce jagged appearance. This blurring changes the character images according to context, and can sometimes fuse them together. In this paper, we offer a low-cost method that can be used as a preprocessing stage, prior to OCR. Our method locates antialiased text in a screen image and segments it into separate character images. Our proposed algorithm significantly improves OCR results, particularly in images with colored text of small font size, such as in graphic user interface (GUI) screens.

Original languageEnglish
Title of host publicationProceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011
Pages424-428
Number of pages5
DOIs
StatePublished - 2 Dec 2011
Externally publishedYes
Event11th International Conference on Document Analysis and Recognition, ICDAR 2011 - Beijing, China
Duration: 18 Sep 201121 Sep 2011

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN (Print)1520-5363

Conference

Conference11th International Conference on Document Analysis and Recognition, ICDAR 2011
Country/TerritoryChina
CityBeijing
Period18/09/1121/09/11

Keywords

  • antialiasing
  • character segmentation
  • text detection

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