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Eighth International Conference on Document Analysis and Recognition (ICDAR'05)
Fast Convolutional OCR with the Scanning N-Tuple Grid
Seoul, Korea
August 31-September 01
ISBN: 0-7695-2420-6
Simon M. Lucas, University of Essex, UK
Kyu Tae Cho, University of Essex, UK

This paper introduces a novel high speed convolutional character recognition system. Convolutional mode operation means that no prior localization or segmentation of characters is required, making this mode extremely robust.

The method uses a 2-d n-tuple grid to sample the image, but decomposes the address calculations into two onedimensional scans. This simple innovation leads to a very fast system, and speeds in excess of 100,000 recognitions per second have been achieved for a 10-class character recognition problem, when operated in convolutional mode.

Quantitative performance results show an error rate of 4.3% on the MNist dataset of isolated hand-written characters. Qualitative results are presented on museum archive card images, indicating that the method has great potential for the character recognition component in a document image analysis system for images of this type.

Citation:
Simon M. Lucas, Kyu Tae Cho, "Fast Convolutional OCR with the Scanning N-Tuple Grid," icdar, pp.799-805, Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005
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