Searching and matching unrecognized handwriting

Abstract

A method and system provide for searching and matching gesture-based data such as handwriting without performing a recognition process on the handwritten gesture data to convert it to a standard computer-coded form. Target data collected as sample data points of spatial coordinates over time are concatenated into a single target gesture sequence of sample data points. The sample data points comprising the gesture-based data structure to be searched (the corpus) are grouped into corpus gesture sequences for matching against the target gesture sequence. Matching may be done by any suitable method, and a novel signal comparison technique based on dynamic time warping concepts is illustrated. The result of the matching is a list of the locations of the matching corpus gesture sequences in the corpus, which in turn may be used for further processing, such as the display of an image of the matching corpus gestures for a system user. The ability to determine the existence and location of a gesture in the corpus that matches a target gesture is the basis for performing a variety of additional functions, such as a 'find and replace' function and the ability to use gestures as keywords to index a gesture-based data structure without performing recognition on either the keyword gestures or the gesture-based data structure. The technique is suitable for inclusion in any system that accepts gesture-based data, such as a personal digital assistant (PDA) or other pen-based computing device.