LAMP Seminar
Language and Media Processing Laboratory
Conference Room 4406
A.V. Williams Building
University of Maryland

Thursday, Feb. 6, 10 AM
Evolution of a Handwritten Word Recognition Algorithm

Paul Gader
Dept. of Computer Engineering and Computer Science
University of Missouri - Columbia


The evolution of a handwritten word recognition algorithm will be described. The algorithm was developed mainly under U. S. Postal Service funding. It is a segmentation-based algorithm that relies on dynamic programming to match the words against lexicons. Several algorithms of this type have been developed by various researchers. However, their performance can vary dramatically. In fact, although the high-level description of our algorithm hasn't changed for several years, its recognition performance has increased dramatically.
In this talk, I will first provide an overview of the system. I will then describe some of the changes that were made to improve its performance. Some of these changes had to do with the character recognizer. A result that was surprising to us at first was that high character recognition rates do not necessarily imply high word recognition rates. Other changes involved using information extracted from multiple character segments simultaneously to measure, within the dynamic programming matcher, the spatial compatibility of a match to a string. Still more changes had to do with methods of aggregating information. We found that robust methods derived from the Choquet integral can achieve better results than traditional methods. Finally, if time permits, I will discuss the problem of combining outputs of several word recognition algorithms using several methods including neural networks, Borda counts, and Choquet integrals.

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