Digitization of historical Chinese documents includes two key technologies, character segmentation and character recognition. This paper focuses on developing character segmentation algorithm. As a preprocessing step, we combine several effective measures to remove noises in a historical Chinese document image. After binarization, a new character segmentation algorithm segment single characters based on projections of a cost image in local windows. The cost image is constructed by utilizing the information of stroke bounding boxes and a skeleton image extracted from the binarized image. We evaluate the proposed algorithm based on matching degrees of character bounding boxes between segmentation results and ground-truth data, and achieve a recall rate of 74.3% on a test set, which shows the effectiveness of the proposed algorithm.

Date Published: 4 February 2013
PDF: 9 pages
Proc. SPIE 8658, Document Recognition and Retrieval XX, 86580O (4 February 2013); doi: 10.1117/12.2008338

Published in SPIE Proceedings Vol. 8658:
Document Recognition and Retrieval XX
Richard Zanibbi; Bertrand Coüasnon, Editor(s)