• DocumentCode
    3695277
  • Title

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

  • Author

    Rachid Hedjam;Hossein Ziaei Nafchi;Reza Farrahi Moghaddam;Margaret Kalacska;Mohamed Cheriet

  • Author_Institution
    Synchromedia Lab, Department of Automated Manufacturing Engineering, ETS, University of Quebec, 1100 Notre-Dame West, Montreal, Canada H3C 1K3
  • fYear
    2015
  • Firstpage
    1181
  • Lastpage
    1185
  • 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    The first competition on the MultiSpectral Text Extraction (MS-TEx) from historical document images has been organized in conjunction with the ICDAR 2015 conference. The goal of this contest is evaluation of the most recent advances in text extraction from historical document images captured by a multispectral imaging system. The MS-TEx 2015 dataset contains 10 handwritten and machine-printed historical document images along with eight spectral images for each image.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.
  • Keywords
    "Image edge detection","Frequency modulation","Image segmentation"
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2015 13th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICDAR.2015.7333947
  • Filename
    7333947