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The first competition on the MultiSpectral Text Extraction (MS-TEx) from historical document images has been organized in conjunction with the ICDAR 2015 conference. The goal of this contest is evaluation of the most recent advances in text extraction from historical document images captured by a multispectral imaging system. The MS-TEx 2015 dataset contains 10 handwritten and machine-printed historical document images along with eight spectral images for each image.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