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ICDAR 2015 contest on MultiSpectral Text Extraction (MS-TEx 2015)

  • Rachid Hedjam
  • , Hossein Ziaei Nafchi
  • , Reza Farrahi Moghaddam
  • , Margaret Kalacska
  • , Mohamed Cheriet
  • École de technologie supérieure
  • McGill University

Research output: Contribution to Book/Report typesContribution to conference proceedingspeer-review

49 Citations (Scopus)

Abstract

The first competition on the MultiSpectral Text Extraction (MS-TEx) from historical document images has been organized in conjunction with the ICDAR 2015 conference. The goal of this contest is evaluation of the most recent advances in text extraction from historical document images captured by a multispectral imaging system. The MS-TEx 2015 dataset contains 10 handwritten and machine-printed historical document images along with eight spectral images for each image. This paper provides a report on the methodology and performance of the five submitted algorithms by various research groups across the world. The objective evaluation and ranking was performed by using well-known evaluation metrics of binarization and classification.

Original languageEnglish
Title of host publication13th IAPR International Conference on Document Analysis and Recognition, ICDAR 2015 - Conference Proceedings
PublisherIEEE Computer Society
Pages1181-1185
Number of pages5
ISBN (Electronic)9781479918058
DOIs
Publication statusPublished - 20 Nov 2015
Event13th IAPR International Conference on Document Analysis and Recognition, ICDAR 2015 - Nancy, France
Duration: 23 Aug 201526 Aug 2015

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2015-November
ISSN (Electronic)2379-2140

Conference

Conference13th IAPR International Conference on Document Analysis and Recognition, ICDAR 2015
Country/TerritoryFrance
CityNancy
Period23/08/1526/08/15

!!!Keywords

  • Document Image Binarization
  • Historical document analysis
  • Multispectral imaging

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