A Flexible Recognition Engine for Complex On-line Handwritten Character Recognition

A major feature of new mobiles terminals using penbased interfaces, such as personal assistants or e-book, is their personal character, implying that a good interface should be easily customizable in order to meet various users’ needs. We proposed recently a new recognition engine with strong adaptation abilities that allows learning a user’s writing style or new symbols easily. It dealt with characters with simple shape only; we describe here an extension of this recognition system that deals with more complex graphical symbols. We propose an adaptive learning scheme that can learn more and more as the writer gives new samples.

• Type: Conference
• Year: 2003
• Where: ICDAR
• Authors: Sanparith Marukatat, Rudy Sicard, Thierry Artières, Patrick Gallinari
• Keywords: Adaptive Learning Scheme, Complex Graphical Symbols, Document Analysis, ICDAR 2003, Strong Adaptation Abilities