Handwriting Quality Evaluation

Authors:
Victor Kulesh;Kevin Schaffer;Ishwar K. Sethi;Mark Schwartz
Affiliations:
-;-;-;-
Venue:
ICAPR '01 Proceedings of the Second International Conference on Advances in Pattern Recognition
Year:
2001

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Abstract

This paper presents an approach to evaluate the quality of handwritten letters based on the set of features that are used by human handwriting experts. The use of these attributes allows very intuitive interpretation of the results and as a consequence provides solid foundation for feedback to the end user of the system. A combination of an artificial neural network and an expert system is used to evaluate and grade each handwritten letter, as well as to provide feedback to the student. The application of such a system would be in the educational field for handwriting teaching and repair.