Summary
In this paper, the author presents the $N Recognizer. This system is built on top of the $1 Recognizer but contains various improvements. $N is capable of recognizing gestures comprised of multiple strokes, recognizing 1D gestures such as lines, and providing bounded rotation invariance to allow for recognition of more symbols. $N also employs two optimization techniques based on the starting angle of a gesture and the number of strokes in a gesture, the second technique being optional. Even though $N is slightly more complex than $1, these optimization techniques help to run faster than $1 since both system are based on template matching.
Discussion
The use of optimization techniques in $N to reduce the number of templates compared greatly helps to reduce the run time of the recognition algorithm. Such techniques could be implemented in other template based recognition systems to reduce the amount of processing required. In order to recognize multi-stroke gestures, $N simply creates multiple templates by connecting the strokes in every possible order. For gestures with three or more strokes this can often greatly increase the number of templates being compared. An alternative method might be to have a single template consisting of only the strokes drawn on the interface and use all possible starting angles when attempting to match to a gesture.
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