Automated entry system for printed documents
Pattern Recognition
Skew correction of document images using interline cross-correlation
CVGIP: Graphical Models and Image Processing
An improved document skew angle estimation technique
Pattern Recognition Letters
A fast approach to the detection and correction of skew documents
Pattern Recognition Letters
Skew Detection of Document Images by Focused Nearest-Neighbor Clustering
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Skew detection using wavelet decomposition and projection profile analysis
Pattern Recognition Letters
Hough transform based fast skew detection and accurate skew correction methods
Pattern Recognition
A method of detecting the orientation of aligned components
Pattern Recognition Letters
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Document skew estimation: an approach based on wavelets
Proceedings of the 2011 International Conference on Communication, Computing & Security
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We present here an enhanced algorithm (e-PCP) for skew detection in scanned documents, based on the work on Piecewise Covering by Parallelogram (PCP) for robust determination of skew angles [C.-H. Chou, S.-Y. Chu, F. Chang, Estimation of skew angles for scanned documents based on piecewise covering by parallelograms, Pattern Recognition 40 (2007) 443-455]. Our algorithm achieves even better robustness for detection of skew angle than the original PCP algorithm. We have shown accurate determination of skew angles in document images where the original PCP algorithm fails. Further, the increased robustness of performance is achieved with reduced number of computation compared to the originally proposed PCP algorithm. The e-PCP algorithm also outputs a confidence measure which is important in automated systems to filter cases where the estimated skew angle may not be very accurate and thus can be handled by manual intervention. The proposed algorithm was tested extensively on all categories of real time documents and comparisons with PCP method is also provided. Useful details regarding faster execution of the proposed algorithm is provided in Appendix.