DocumentCode
2022020
Title
An EM Based Algorithm for Skew Detection
Author
Egozi, A. ; Dinstein, Itshak
Author_Institution
Ben-Gurion Univ. of the Negev, Beer-Sheva
Volume
1
fYear
2007
fDate
23-26 Sept. 2007
Firstpage
277
Lastpage
281
Abstract
We present a a statistical approach to skew detection, where the textual features of a document image are modeled as a mixture of straight lines in Gaussian noise. The EM algorithm is used to estimate the parameters of the mixture model and the skew angle estimate is extracted from the estimated parameters. Experiments prove that our method has some advantages over other existing methods in terms of accuracy and efficiency.
Keywords
Gaussian noise; document image processing; expectation-maximisation algorithm; parameter estimation; Gaussian noise; document image textual feature; expectation maximization algorithm; parameter estimation; skew angle estimate; skew detection; Algorithm design and analysis; Character recognition; Clustering algorithms; Detection algorithms; Digital images; Gaussian noise; Least squares methods; Maximum likelihood estimation; Nearest neighbor searches; Parameter estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International Conference on
Conference_Location
Parana
ISSN
1520-5363
Print_ISBN
978-0-7695-2822-9
Type
conf
DOI
10.1109/ICDAR.2007.4378719
Filename
4378719
Link To Document