2013 12th International Conference on Document Analysis and Recognition (2003)
Aug. 3, 2003 to Aug. 6, 2003
Chew Lim Tan , National University of Singapore
Yue Lu , National University of Singapore
The nearest-neighbor based document skew detection methods do not require the presence of a predominant text area, and are not subject to skew angle limitation. However, the accuracy of these methods is not perfect in general. In this paper, we present an improved nearest-neighbor based approach to perform accurate document skew estimation. Size restriction is introduced to the detection of nearest-neighbor pairs. Then the chains with a largest possible number of nearest-neighbor pairs are selected, and their slopes are computed to give the skew angle of document image. Experimental results on various types of documents containing different linguistic scripts and diverse layouts show that the proposed approach has achieved an improved accuracy for estimating document image skew angle and has an advantage of being language independent.
Chew Lim Tan, Yue Lu, "Improved Nearest Neighbor Based Approach to Accurate Document Skew Estimation", 2013 12th International Conference on Document Analysis and Recognition, vol. 01, no. , pp. 503, 2003, doi:10.1109/ICDAR.2003.1227716