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ICDAR
2003
IEEE

Training on Severely Degraded Text-Line Images

14 years 4 months ago
Training on Severely Degraded Text-Line Images
We show that document image decoding (DID) supervised training algorithms, as a result of recent refinements, achieve high accuracy with low manual effort even under conditions of severe image degradation in both training and test data. We describe improvements in DID training of character template, set-width, and channel (noise) models. Large-scale experimental trials, using synthetically degraded images of text, have established two new and practically important advantages of DID algorithms:
Prateek Sarkar, Henry S. Baird, Xiaohu Zhang
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ICDAR
Authors Prateek Sarkar, Henry S. Baird, Xiaohu Zhang
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