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Approximate stroke sequence string matching algorithm for character recognition and analysis

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3 Author(s)
Sung-Hyuk Cha ; Center of Excellence for Document Anal. & Recognition, State Univ. of New York, Buffalo, NY, USA ; Yong-Chul Shin ; S. N. Srihari

Given two character images, we would like to measure their similarity or difference. Such a similarity or difference measure facilitates the solution to character recognition and handwriting analysis problems. There is, however, no universal definition for similarity measure satisfying a wide range of characteristics such as the slant, deformation or other invariant constraints. For this reason, we propose a new definition for the character similarity measure. First, the proposed method converts a two-dimensional image into a one-dimensional string. Next, it computes the edit distance by the modified approximate string matching algorithm. We describe how to extract the string information and compute the distance and then present the details of applications in handwriting analysis and both online and offline character recognition

Published in:

Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on

Date of Conference:

20-22 Sep 1999