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The target of this recognition system is the set of handwritten Chinese characters input from tablet devices with stroke-sequence and stroke-count being free but within the constraint of normal writing.

A formalism based upon an initial stroke-sequence decision tree and position matching has been developed for recognizing handwritten Chinese characters. This formalism has the advantages of using the features of strokes, stroke-sequence, and geometric relations but avoids the disadvantages caused by the instability of all of the above features. With extensive training, it can be proven that this formalism may provide a very promising result even in handling erroneous writing such as missing a stroke, wrong writing sequence etc.

This paper describes our research to enhance handwriting-based user interfaces. It consists of building infrastructures, advancing handwriting recognition technology, studying human interface and developing applications. Our goal is to provide consistent and creative human interfaces among a wide range of pen input devices such as PDA, desktop tablet and electronic whiteboard. The on-line handwritten character recognition is the key technology. Our method has marked 90 to 95% correct recognition rates without learning to a large database of on-line handwritten Japanese text. Its recognition speed is about 0.02 sec/character on a Pentium 200 Mhz processor and roughly 0.2 sec/char, on a small PDA machine. The method is not only robust to stroke connections and pattern distortions but also highly customizable for personal use. Upon the request of learning an input pattern, it identifies a deformed subpattern (radical), registers the (sub)pattern and extends the effect to all the character categories whose shapes include it. This paper also describes educational applications which benefit from pen interfaces and the handwriting recognition engine.

The target of this recognition system is the set of handwritten Chinese characters input from tablet devices with stroke-sequence and stroke-count being free but within the constraint of normal writing.

A formalism based upon an initial stroke-sequence decision tree and position matching has been developed for recognizing handwritten Chinese characters. This formalism has the advantages of using the features of strokes, stroke-sequence, and geometric relations but avoids the disadvantages caused by the instability of all of the above features. With extensive training, it can be proven that this formalism may provide a very promising result even in handling erroneous writing such as missing a stroke, wrong writing sequence etc.