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Summary:
Kara and Stahovich present a vision-based trainable symbol recognizer. The recognizer is scale, translation, and rotation invariant, and runs very quickly. The system is an instance-based classifier, so it is easy to add new classes or new training instances of already-defined classes.
Discussion:
This paper presents a good symbol recognizer that's pretty easy to implement. It's also a good introduction to a number of interesting distance metrics.
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