DocumentCode :
2144142
Title :
A Novel Skew Detection Technique Based on Vertical Projections
Author :
Papandreou, A. ; Gatos, B.
Author_Institution :
Comput. Intell. Lab., Nat. Res. Center Demokritos, Athens, Greece
fYear :
2011
fDate :
18-21 Sept. 2011
Firstpage :
384
Lastpage :
388
Abstract :
Document skew detection is often done by the use of horizontal projections. In this paper, we introduce a new document skew detection approach that is based on vertical projections as well as bounding box minimization criterion. We motivated by the fact that the majority of the Latin characters have vertical strokes. We claim that the proposed approach is more efficient and gives more accurate results compared with the state-of-the-art skew detection algorithm based on horizontal projections since it is noise and warp resistant. For these reasons, it can be efficiently applied to historical machine printed documents. Experimental results on a database with representative historical printed documents prove the efficiency of the proposed approach. Moreover, an analysis of the performance of the main elements of the proposed technique is also done.
Keywords :
document image processing; minimisation; Latin characters; bounding box minimization criterion; document skew detection approach; historical machine printed documents; horizontal projections; vertical projections; vertical strokes; Accuracy; Estimation; Histograms; Image segmentation; Minimization; Noise; Text analysis; Document Skew Detection; Historical Document Image Processing; Vertical Image Projections;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
ISSN :
1520-5363
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2011.85
Filename :
6065340
Link To Document :
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