Generating realistic Kanji character images from on-line patterns
Ondrej Velek, Cheng-Lin Liu, Masaki Nakagawa · 2002
The availability of a large sample database is very important to design high accuracy classifiers for handwritten character recognition. Collecting image samples from human writers and practical documents is expensive particularly for large character sets, like with East-Asia-languages. We can therefore take advantage of existing online databases to generate additional off-line images. This paper proposes a method to generate realistic character images from online patterns. From the pen trajectory of an online pattern, the proposed method can generate numerous images of various stroke shapes using three painting modes: constant line mode, proportional mode and calligraphic mode. Particularly, the calligraphic mode combines the pen trajectory (representing the writing style of one concrete writer) with real stroke images (also representing individual writing style of a concrete writer) to generate character images that look as if they were produced with a brush or pen by human hand.