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
Digital Document Processing
A nearest-neighbor chain based approach to skew estimation in document images
Pattern Recognition Letters
A method of detecting the orientation of aligned components
Pattern Recognition Letters
Hough transform based fast skew detection and accurate skew correction methods
Pattern Recognition
An adaptive technique for global and local skew correction in color documents
Expert Systems with Applications: An International Journal
Fast and robust skew estimation of scanned documents through background area information
Pattern Recognition Letters
Skew estimation of document images using bagging
IEEE Transactions on Image Processing
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Skew angle estimation is an important component of optical character recognition (OCR) systems and document analysis systems (DAS). In this paper, a novel and an efficient method to estimate the skew angle of a scanned document image is proposed. The proposed method has two stages. In first stage, using boundary-growing approach, text lines containing characters of the scanned document image are extracted. From each text line, coordinates of the positions of the characters are obtained. In second stage, the obtained coordinates are fed to linear regression analysis (LRA) for the purpose of computation of skew angle. Several experiments have been conducted on various types of documents such as documents containing different language texts, documents with different fonts and documents with noise to reveal the robustness of the proposed method. A comparative study with the well-known methods is presented to show that the proposed method is superior in terms of accuracy and computational efficiency. fficiency.