Indirect Symbolic Correlation Approach to Unsegmented Text Recognition

Authors

George Nagy, Rensselaer Polytechnic InstituteFollow
Sharad C. Seth, University of Nebraska-LincolnFollow
Y. Lin, University of Nebraska-LincolnFollow
Shashank K. Mehta, Indian Institute of Technology, KanpurFollow

Date of this Version

2003

Comments

Published in Proceedings of the 2003 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW’03). Copyright 2003 IEEE. Used by permission.

Abstract

The new non-parametric approach to unsegmented text recognition builds two bipartite graphs that result from the feature-level and lexical comparisons of the same word against a reference string which need not include the query word. The lexical graph preserves the relative order of edges in the feature graph corresponding to correctly recognized features. This observation leads to a subgraph-matching formulation of the recognition problem. An initial implementation proves the robustness of the approach for up-to 20% noise introduced in the feature-level graph.