Learn More
Calligraphic style is considered, for this research, visual attributes of images of calligraphic characters sampled randomly from a " work " created by a single artist. It is independent of page layout or textual content. An experimental design is developed to investigate to what extent the source of a single, or of a few pairs, of character images can be(More)
A set of 13,351 digitized calligraphic characters were segmented and labeled, with 12,918 characters extracted from 21 books scanned by the CADAL scanning center located in Zhejiang University's library, and 1443 characters from calligraphy works from web sources. The database contains calligraphy from 208 works, some from over 1000 years ago. Statistics(More)
—Calligraphic data entry is accelerated by generating, with a feature-based character classifier, an ordered list of reference candidate labels for each character image. The improvement of labeling throughput depends on the top-N accuracy of the classifier, which in turn is a function of the available already-labeled patterns. Experiments on a database of(More)
A large collection of reproductions of calligraphy on paper was scanned into images to enable web access for both the academic community and the public. Calligraphic paper digitization technology is mature, but technology for segmentation, character coding, style classification, and identification of calligraphy are lacking. Therefore, computational tools(More)