DocumentCode :
3638239
Title :
Text line processing for high-confidence skew detection in image documents
Author :
Daniel Rosner;Costin-Anton Boiangiu;Alexandru Ştefănescu;Nicolae Ţăpuş;Alexandra Olteanu
Author_Institution :
Computer Science Department, Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Splaiul Independentei 313, Sector 6, 060042, Romania
fYear :
2010
Firstpage :
129
Lastpage :
132
Abstract :
Skew detection and correction is an important step in automated content conversion systems, on which overall system performance is dependent. Although there are many working solutions at the present time, the search for an algorithm that can achieve good error rates in a fast running time and on different layout types is still open, so new solutions for skew detection are needed. The paper at hand presents a neighbor clustering based approach that has the classical advantages of this class of algorithms - the speed, but delivers better accuracy, comparable with that of Hough based solutions.
Keywords :
"Pixel","Accuracy","Clustering algorithms","Estimation","Nearest neighbor searches","Heuristic algorithms","Algorithm design and analysis"
Publisher :
ieee
Conference_Titel :
Intelligent Computer Communication and Processing (ICCP), 2010 IEEE International Conference on
Print_ISBN :
978-1-4244-8228-3
Type :
conf
DOI :
10.1109/ICCP.2010.5606448
Filename :
5606448
Link To Document :
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