Japanese / English

Detail of Publication

Text Language English
Authors Seiichi Uchida, Megumi Sakai, Masakazu Iwamura, Shinichiro Omachi, and Koichi Kise
Title Skew Estimation by Instances
Journal Proceedings of the 8th IAPR International Workshop on Document Analysis Systems (DAS2008)
Pages pp.201-208
Reviewed or not Reviewed
Month & Year September 2008
Abstract This paper proposes a novel skew estimation method by instances. The instances to be learned (i.e., stored) are rotation invariants and a rotation variant for each character category. Using the instances, it is possible to estimate a skew angle of each individual character on a document. This fact implies that the proposed method can estimate the skew angle of a document where characters do not form long straight text lines. Thus, the proposed method will be applicable to various documents such as signboard images captured by a camera. Experimental evaluation using synthetic and real images revealed the expected robustness against various character layouts.
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