Algorithm of document skew detection based on character vertices
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Fast and robust skew estimation of scanned documents through background area information
Pattern Recognition Letters
Recognition driven page orientation detection
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Statistical mixture model for documents skew angle estimation
Pattern Recognition Letters
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
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This paper presents a document skew and orientation de- tection technique. The proposed technique estimates docu- ment skew and orientation based on the observation that text images normally hold a large amount of equidistant in- terline spacings and the number of character ascenders is statistically much larger than that of character descenders. Given a document image with arbitrary skew and orien- tation, white run histograms are first constructed through scanning documents in horizontal and vertical directions. Document skew is then estimated by using the white runs that exactly span the interline spacing. Lastly, document orientation is determined according to the numbers of char- acter ascenders and descenders, which are detected by us- ing the white runs that cross the interline spacing and lie over character ascenders and descenders. Experiments show that the proposed technique is fast, accurate, and ca- pable of detecting arbitrary document skew and orientation.