Supporting electronic ink databases

The emergence of the pen as the main interface device for personal digital assistants and pen-computers has made handwritten text, and more generally ink, a first-class object. As for any other type of data, the need of retri eval is a prevailing one. Retrieval of handwritten text is more difficult t han that of conventional data since it is necessary to identify a handwritt en word given slightly different variations in its shape. The current way o f addressing this is by using handwriting recognition, which is prone to er rors and limits the expressiveness of ink. Alternatively, one can retrieve from the database handwritten words that are similar to a query handwritten word using techniques borrowed from pattern and speech recognition. In thi s paper, an indexing technique based on Hidden Markov Models is proposed. I ts implementation and its performance is reported in this paper. Copyright (C) 1999 Published by Elsevier Science Ltd.