Handwritten Hangul Character Recognition with Hierarchical Stochastic Character Representation

In structural character recognition, a character is usually viewed as a set of strokes and the spatial relationships between them. In this paper, we propose a stochastic modeling scheme by which strokes as well as relationships are represented by utilizing the hierarchical characteristics of target characters. Based on the proposed scheme, a handwritten Hangul (Korean) character recognition system is developed. The effectiveness of the proposed scheme is shown through experimental results conducted on a public database.

• Type: Conference
• Year: 2003
• Where: ICDAR
• Authors: Kyung-Won Kang, Jin Hyung Kim
• Keywords: Character Recognition, Document Analysis, ICDAR 2003, Stochastic Modeling Scheme, Structural Character Recognition