Title: cBAD: ICDAR2017 Competition on Baseline Detection
Language: English
Authors: Diem, Markus  
Kleber, Florian  
Fiel, Stefan 
Grüning, Tobias 
Gatos, Basilis 
Issue Date: 2017
Citation: 
Diem, M., Kleber, F., Fiel, S., Grüning, T., & Gatos, B. (2017). cBAD: ICDAR2017 Competition on Baseline Detection. In 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR). Kyoto. https://doi.org/10.1109/ICDAR.2017.222
Abstract: 
The cBAD competition aims at benchmarking state-of-the-art baseline detection algorithms. It is in line with previous competitions such as the ICDAR 2013 Handwriting Segmentation Contest. A new, challenging, dataset was created to test the behavior of state-of-the-art systems on real world data. Since traditional evaluation schemes are not applicable to the size and modality of this dataset, we present a new one that introduces baselines to measure performance. We received submissions from five different teams for both tracks.
Keywords: cBAD; baseline detection; text-line detection
URI: https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:3-3384
http://hdl.handle.net/20.500.12708/881
Library ID: AC11365321
ISBN: 9781538635865
Organisation: E193 - Institut für Rechnergestützte Automation 
Publication Type: Inproceedings
Konferenzbeitrag
Appears in Collections:Conference Paper

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