DocumentCode :
3695271
Title :
ICDAR2015 competition on recognition of documents with complex layouts - RDCL2015
Author :
A. Antonacopoulos;C. Clausner;C. Papadopoulos;S. Pletschacher
Author_Institution :
Pattern Recognition and Image Analysis (PRImA) Research Lab, School of Computing, Science and Engineering, University of Salford, Greater Manchester, M5 4WT, United Kingdom
fYear :
2015
Firstpage :
1151
Lastpage :
1155
Abstract :
This paper presents an objective comparative evaluation of page segmentation and region classification methods for documents with complex layouts. It describes the competition (modus operandi, dataset and evaluation methodology) held in the context of ICDAR2015, presenting the results of the evaluation of eight methods - four submitted, two state-of-the-art systems (one commercial and one open-source) and their two immediately previous versions. Three scenarios are reported in this paper, one evaluating the ability of methods to accurately segment regions and two evaluating both segmentation and region classification (one with emphasis on text and the other focusing only on text). The results indicate that an innovative approach has a clear advantage but there is still a considerable need to develop robust methods that deal with layout challenges, especially with the non-text content.
Keywords :
Optical character recognition software
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2015 13th International Conference on
Type :
conf
DOI :
10.1109/ICDAR.2015.7333941
Filename :
7333941
Link To Document :
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