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Automatic Text Recognition in Web Images

Published: 17 October 2017 Publication History

Abstract

Web images play an important role in delivering multimedia content on the Web. The text embedded in web images carry semantic information related to layout and content of the pages. Statistics show that there is a significant need to detect and recognize text from web images. This paper presents an architecture that efficiently integrates localization, extraction and recognition algorithms applied to text recognition in web images. In the recognition step is proposed a procedure based on super-resolution and an iterative method for improving the performance. The approach is implemented and evaluated using Matlab and cloud computing, making the system flexible, scalable and robust in detecting texts from complex web images with different orientations, dimensions and colors. Competitive results are presented, both in precision and recognition rate, when compared with other systems in the existing literature.

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Cited By

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  • (2024)Text to voice conversion of text embedded in images2024 IEEE International Conference for Women in Innovation, Technology & Entrepreneurship (ICWITE)10.1109/ICWITE59797.2024.10503275(148-154)Online publication date: 16-Feb-2024
  • (2023)Robust Perception and Visual Understanding of Traffic Signs in the WildIEEE Open Journal of Intelligent Transportation Systems10.1109/OJITS.2023.32980314(611-625)Online publication date: 2023
  • (2019)Text Extraction and Clustering for Multimedia: A review on Techniques and Challenges2019 International Conference on Digitization (ICD)10.1109/ICD47981.2019.9105905(38-43)Online publication date: Nov-2019

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cover image ACM Other conferences
WebMedia '17: Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web
October 2017
522 pages
ISBN:9781450350969
DOI:10.1145/3126858
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • SBC: Brazilian Computer Society
  • CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
  • CGIBR: Comite Gestor da Internet no Brazil
  • CAPES: Brazilian Higher Education Funding Council

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2017

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Author Tags

  1. text detection
  2. text recognition.
  3. web images

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  • Short-paper

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Webmedia '17
Sponsor:
  • SBC
  • CNPq
  • CGIBR
  • CAPES
Webmedia '17: Brazilian Symposium on Multimedia and the Web
October 17 - 20, 2017
RS, Gramado, Brazil

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WebMedia '17 Paper Acceptance Rate 38 of 138 submissions, 28%;
Overall Acceptance Rate 270 of 873 submissions, 31%

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Cited By

View all
  • (2024)Text to voice conversion of text embedded in images2024 IEEE International Conference for Women in Innovation, Technology & Entrepreneurship (ICWITE)10.1109/ICWITE59797.2024.10503275(148-154)Online publication date: 16-Feb-2024
  • (2023)Robust Perception and Visual Understanding of Traffic Signs in the WildIEEE Open Journal of Intelligent Transportation Systems10.1109/OJITS.2023.32980314(611-625)Online publication date: 2023
  • (2019)Text Extraction and Clustering for Multimedia: A review on Techniques and Challenges2019 International Conference on Digitization (ICD)10.1109/ICD47981.2019.9105905(38-43)Online publication date: Nov-2019

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