A multiscale approach for recognizing complex annotations in engineering documents

Laine, Andrew F.; Ball, William; Kumar, Arun

A novel method for character recognition targeted at complex annotations found in engineering documents is presented. A feasibility study is described in which characters extracted from engineering drawings were recognized without error from a class of 36 distinct alphanumeric patterns by a neural network classifier trained with multiscale representations. An incremental strategy is presented for resolution which relies upon the continuity between hierarchical levels of a novel multiscale decomposition. The authors observed a 16-fold reduction in the amount of information needed to represent each character for recognition. These results suggest high reliability at a reduced cost of representation.


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Proceedings, CVPR '91 : June 3-6, 1991, Lahaina, Maui, Hawaii

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Academic Units
Biomedical Engineering
Published Here
August 18, 2010