Local descriptors for document layout analysis

Authors:
Angelika Garz;Markus Diem;Robert Sablatnig
Affiliations:
Institute of Computer Aided Automation, Computer Vision Lab, Vienna University of Technology, Austria;Institute of Computer Aided Automation, Computer Vision Lab, Vienna University of Technology, Austria;Institute of Computer Aided Automation, Computer Vision Lab, Vienna University of Technology, Austria
Venue:
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
Year:
2010

Citing 5
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Abstract

This paper presents a technique for layout analysis of historical document images based on local descriptors. The considered layout elements are regions of regular text and elements having a decorative meaning such as headlines and initials. The proposed technique exploits the differences in the local properties of the layout elements. For this purpose, an approach drawing its inspiration from state-of-the-art object recognition methodologies - namely Scale Invariant Feature Transform (Sift) descriptors - is proposed. The scale of the interest points is used for localization. The results show that the method is able to locate regular text in ancient manuscripts. The detection rate of decorative elements is not as high as for regular text but already yields to promising results.