Research On Several Problems Of Chinese Character Keyboard Input And Non-keyboard Input

The thesis has maily been research in the implementaion of Chinese character input methods which can be mastered without a specialized leaming,including keyboard input and OLCCRAfter studying the structure of Chinese character,we have classified Chinese character strokes and coded Chinese character with stroke strings. Our basic work has also included compiling a stroke coding dictionary for Chinese National Standard Code For Information Interchange (GB23 12-80) and making statistics on stroke imformation.On the basis of the coding dictionary and statistical data,we have devised a keyboard input method and designed a kind of key arrangement for the method.To avoid inputting the stroke strings completely while inputting a Chinese character, we have a requirement of missing some elements in Chinese character input codes. So a fast pattern matching algorithm on mass string assemble has been proposed to solve the problem of fuzzy matching between a string pattern and a string assemble.To make the algorithm cost-effective in space and time,we have developed an optimized trie-tree structure to store the string assemble and introduced the Knuth-Morris-Pratt(KMP) and Finite-Automata(FA) string matching thought to our algorithm.The algorithm has been describled in details and the cost of space and run time has been analized in the thesis.In order to input Chinese character naturally from keyboard,our next step is presenting a new input method named "stroke simulation".The main idea of the method is inputting the feature points of a stroke,such as up-point, twist-point and down-point, instead of inputting a stroke directly from keyboard. The trail of the feature points we extracted from a stroke shoud be able to shape the stroke. The most attractive point of this method is that it allows users input strokes continually without an extra key to separate two continuous strokes. In addition,the method supports deleting strokes backwards to make users be able to modify the error input. Except for PCs,this new method is fit for applicating on some portable device with number keyboard,such as mobile phone,electronical dictionary,etc.It can be viewed as an transitional step towards OLCCR.The final work we have done is a preliminary implementation of OLCCR based on the stroke coding dictionary which had been presented before.Our method is to extract the feature points from the trails of the strokes.The feature points formed the stroke segments,the stroke segments formed the strokes. We recognize hand-written Chinese character from the stroke imformation we have obtained from the original inputting points.