Summary
In this paper, the author describes a new method in which to classify shape strokes and text strokes. Instead of using multiple features as past classifiers have done, the new method relies on the single feature of stroke entropy. Strokes are first grouped based on temporal and spatial information and then stroke entropy is calculated for each group. If the group stroke entropy is above a certain threshold, it is classified as text or classified as a shape if the entropy is below a certain threshold. Anything in between the thresholds is classified as unknown.
Discussion
The use of entropy to classify text and shape objects appears to be a very useful feature which provided favorable recognition rates. Text recognition rates were quite high, and while shape recognition rates were higher than previous studies, perhaps extra features could be checked when a group of strokes is unable to be classified to determine which category of classification should be favored.
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