Prototype Pruning by Feature Extraction for Handwritten Mathematical Symbol Recognition

Comments

Yuxiang's blog

Summary

In this paper the author discusses the problem of recognizing math symbols. The problem is tough because there are around 1000 to 2000 mathematics symbols today. Mathematics writing is a blend of drawing and writing. In this paper the author defines some features related to mathematics symbols, gives algorithms to extract those and use these features to recognize the symbols.
In preprocessing the collected data the author describes some techniques he used. Techniques used are chopping head & tail, re-sampling, smoothing and size normalization. Author also identifies some features which he categorized in these broad categories.

1. Geometric features
2. Ink related features
3. Directional features
4. Global features

The recognition method he used was elastic matching, which is to determine the minimum distance between the unknown symbols and a set of models.

Discussion

This paper discusses some new set of features which might feel more relevant to the mathematics symbols but are also good for other set of sketches