On-line handwritten Kanji string recognition based on grammar description of character structures

In this paper, we evaluate a method for on-line handwritten Kanji character recognition by describing the structure of Kanji using Stochastic Context-Free Grammar (SCFG), and extend it in order to recognize Kanji strings. In this method, we turn attention to the hierarchical structure of Kanji characters which consist of character-parts and strokes, and consider all character patterns or strings to be generated from SCFG with stochastic stroke shape and position relationship between character-parts. Describing Kanji with a few stroke shape and relative position labels, the method enables efficient training and thus robust recognition. We evaluated the recognition performance on several domains of Kanji, and on Kanji strings consist of 2 or 3 characters and gained the recognition rate of 99.29 – 97.40% for characters and 90.80% for strings.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Ikumi Ota, Ryo Yamamoto, Takuya Nishimoto, Shigeki Sagayama
• Keywords: Computer Vision, ICPR 2008, Kanji Character Recognition, Kanji Characters, Kanji Strings