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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

Résultats de recherche: Chapitre dans un livre, rapport, actes de conférenceParticipation à un ouvrage collectif lié à un colloque ou une conférenceRevue par des pairs

48 Citations (Scopus)

Résumé

The first competition on the MultiSpectral Text Extraction (MS-TEx) from historical document images has been organized in conjunction with the ICDAR 2015 conference. The goal of this contest is evaluation of the most recent advances in text extraction from historical document images captured by a multispectral imaging system. The MS-TEx 2015 dataset contains 10 handwritten and machine-printed historical document images along with eight spectral images for each image.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.

langue originaleAnglais
titre13th IAPR International Conference on Document Analysis and Recognition, ICDAR 2015 - Conference Proceedings
EditeurIEEE Computer Society
Pages1181-1185
Nombre de pages5
ISBN (Electronique)9781479918058
Les DOIs
étatPublié - 20 nov. 2015
Evénement13th IAPR International Conference on Document Analysis and Recognition, ICDAR 2015 - Nancy, France
Durée: 23 août 201526 août 2015

Série de publications

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

Conférence

Conférence13th IAPR International Conference on Document Analysis and Recognition, ICDAR 2015
Pays/TerritoireFrance
La villeNancy
période23/08/1526/08/15

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