TY - GEN
T1 - Skew estimation and correction for form documents using wavelet decomposition
AU - Xi, Dihua
AU - Kamel, Mohamed
AU - Lee, Seong Whan
PY - 2005
Y1 - 2005
N2 - Form document image processing has become an increasingly essential technology in office automation tasks. One of the problems is that the document image may appear skewed for many reasons. Therefore, the skew estimation plays an important role in any automatic document analysis system. In the past few years, many algorithms have been developed to detect the skew angle of text document images. However, these algorithms suffer from two major deficiencies. Firstly, most of them suppose that the original image is monochrome and therefore they are not suitable to apply to documents with a complicated background. Secondly, most of the current methods were developed for general document images that are not as complicated as form documents. In this paper, we present a new approach to skew detection for grey-level form document images. In our system, image decomposition by 2D wavelet transformations is used to estimate the skew angle.
AB - Form document image processing has become an increasingly essential technology in office automation tasks. One of the problems is that the document image may appear skewed for many reasons. Therefore, the skew estimation plays an important role in any automatic document analysis system. In the past few years, many algorithms have been developed to detect the skew angle of text document images. However, these algorithms suffer from two major deficiencies. Firstly, most of them suppose that the original image is monochrome and therefore they are not suitable to apply to documents with a complicated background. Secondly, most of the current methods were developed for general document images that are not as complicated as form documents. In this paper, we present a new approach to skew detection for grey-level form document images. In our system, image decomposition by 2D wavelet transformations is used to estimate the skew angle.
UR - http://www.scopus.com/inward/record.url?scp=33645992733&partnerID=8YFLogxK
U2 - 10.1007/11559573_23
DO - 10.1007/11559573_23
M3 - Conference contribution
AN - SCOPUS:33645992733
SN - 3540290699
SN - 9783540290698
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 182
EP - 190
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 2nd International Conference on Image Analysis and Recognition, ICIAR 2005
Y2 - 28 September 2005 through 30 September 2005
ER -