Publication
Recognition Driven Page Orientation Detection
Yves Rangoni; Faisal Shafait; Joost van Beusekom; Thomas Breuel
In: Proceedings of the 2009 IEEE International Conference on Image Processing. IEEE International Conference on Image Processing (ICIP-2009), November 7-10, Cairo, Egypt, IEEE, 11/2009.
Abstract
In document image recognition, orientation detection of the
scanned page is necessary for the following procedures to
work correctly as they assume that the text is well oriented.
Several methods have been proposed, but most of them rely
on heuristics of the script such as the graphical asymmetry be-
tween ascenders and descenders for Roman script. The litera-
ture shows that as soon as this assumption is not fulfilled, e.g.
plain capital text, noisy or degraded characters, etc. they fail.
For a large-scale digitalization process, a low error and rejec-
tion rate are expected in order to reduce the amount of human
intervention. We propose a Recognition Driven Page Orienta-
tion Detection (RD-POD) which does not depend on external
criteria or assumption on the shape of the script. It uses the
OCR engine for estimating the right orientation with a few
lines of the document image. The RD-POD is highly robust
and accurate, and is able to detect multiple orientations. Ex-
perimental evaluation shows that our method outperforms the
current state-of-the-art on UW-1 dataset with an accuracy of
99.7%. Further tests on other three large and public datasets
(MARG, ICDAR07, Google 1000 books) show accuracies of
above 99% on each of them.