Cursive word skew/slant corrections based on Radon transform

Authors:
Jian-xiong Dong;Ponson Dominique;Adam Krzyyzak;Ching Y. Suen
Affiliations:
IMDS Software;IMDS Software;CENPARMI, Concordia University, Montreal;CENPARMI, Concordia University, Montreal
Venue:
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Year:
2005

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Abstract

This paper presents two fast and robust algorithms for word skew and slant corrections based on Radon transform. For the skew correction, we maximize a global measure which is defined by Radon transform of image and its gradient to estimate the slope. For the slant correction, Radon transform is used to estimate the long strokes and a word slant is measured by the average angle of these long strokes. Compared with the previous methods, these two algorithms do not require the setting of parameters heuristically. Moreover, the algorithms perform well on words of short length, where the traditional methods usually fail.