HBR2013 follows the successful running of all previous ICDAR Page Segmentation competitions, and expands the scope to historical books with distortions.
Layout Analysis and Text Recognition are of fundamental importance among Document Image Analysis steps and have been (and continue to be) relatively well researched. Historical documents are of particular interest as they pose a number of challenges and, at the same time, represent a very large proportion of printed documents in existence. With the increasing number of digitisation projects initiated by libraries world-wide, the problem of analysis and recognition of these documents is very topical.
Historical books represent a large proportion of libraries’ holdings and continue to be the focus of large-scale digitisation projects. A number of distortions frequently manifest themselves in scans of historical books, hindering layout analysis and text recognition. The motivation of the competition is to evaluate existing approaches using a realistic dataset and an objective performance analysis system.
HBR2013 follows the successful running of all previous ICDAR Page Segmentation competitions (2001, 2003, 2005, 2009 and 2011). The proposed competition will expand the scope to historical books with distortions (the historical documents in the dataset of the ICDAR2011 competition were largely distortion free – in order to better evaluate the segmentation step on its own). Furthermore, the breadth of the competition will increase to cover recognition as well.