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