Reading #13. Ink Features for Diagram Recognition (Plimmer)

Comment Location:
http://pacocomputer.blogspot.com/2010/11/reading-13-ink-features-for-diagram.html

Summary:
The author attempted to distinguish between text and shapes.  The author attempted a linear split of the data.  First, the data is protted onto a graph according to its "bounding box width"; then the best fit vertical line is placed and the strokes are classified depending on which side of the line they are located.  The initial results showed a large number of misclassifications, particularly in the shape department.  The text had a much lower misclassification rate.

I did not find a step-by-step algorithm on how the bounding box was calculated.  I noticed Figure 3 revealed some information about the bounding box.  It seems the bounding box is a summary of the features of a given stroke.  Inter-stroke gaps (distance between strokes) was the biggest key feature of the feature set; it is smaller from text-to-text than shape-to-shape.

Here are the significant features:

Interstroke gaps: Time till next stroke, Speed till next stroke, Distance from last stroke, Distance to next stroke
Size: Bounding box width, Perimeter to area, Amount of ink inside
Curvature: Total angle

Discussion:
This algorithm has immediate potential for the 2nd programming project.  I plan on doing one of the sets involving characters, so this algorithm warrants close examination.  I am dissappointed in the results, but there is potential.  The author managed to find text remarkably well.  If an additional filter is used to eliminate the misclassified shapes, then the results will improve significantly.