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Accuracy; Estimation; Histograms; Image segmentation; Minimization; Noise; Text analysis; Document Skew Detection; Historical Document Image Processing; Vertical Image Projections;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
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