Skew correction of document images using interline cross-correlation
CVGIP: Graphical Models and Image Processing
Skew Angle Detection of Digitized Indian Script Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Robust Skew Detection Algorithm for Grayscale Document Image
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
A Range Free Skew Detection Technique for Digitized Gurmukhi Script Documents
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
An Enhanced Skew Angle Estimation Technique for Binary Document Images
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Multi-Skew Detection of Indian Script Documents
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Improved Nearest Neighbor Based Approach to Accurate Document Skew Estimation
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Perceptive Vision for Headline Localisation in Bangla Handwritten Text Recognition
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
Hough transform based fast skew detection and accurate skew correction methods
Pattern Recognition
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During scanning of documents the image may get skewed because of improper alignment of paper on the scanner, which results in wrong alignment of text on the document image. In some cases the image may even have double skew both at the page level and at word level due to curl near the binding of the book or in old typed/printed documents. Therefore skew detection and correction becomes an indispensable pre-processing task before the recognition of the text. In this paper we have proposed a robust technique for skew detection and correction of isolated words of machine printed Gurmukhi documents. The method presented here relies on the structural properties of words in Indic Script. The algorithm first identifies skewed word and then corrects the skewed words only. According to the proposed technique, isolated words having straight headline are not considered skewed but when length of headline is less than a threshold value then the word may be skewed and becomes target for correction. The algorithm can be equally effective for machine printed documents of those scripts where headline is used to connect characters of a word.