Reading #14: Using Entropy to Distinguish Shape Versus Text in Hand-Drawn Diagrams (2009)

by Akshay Bhat and Tracy Hammond

Comments: Ayden

The authors propose that entropy rates are higher for text strokes than for non-text strokes and attempt to separate shapes from text using this idea. They achieved a 92% recognition rate. They define entropy, calculate entropy for all letters of the alphabet, and perform classification on collected sketches.

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I agree that text shapes have high entropy, and it is interesting to note that this approach has not been taken earlier in the history of sketch recognition. Obviously some primitive shapes, such as circle and rectangle, will have lower entropy than text, but what about helixes or more complex shapes? This might be good in some diagramming domains.