Is quantity better than quality? — A study case on a simple classifier applied to digit character recognition —
Journal
Technical Report of IEICE
Presentation number
PRMU2010-65
Reviewed
Not reviewed
Date
September 2010
Research fields
Pattern recognition
Key
Barrat2010 (id=1204)
Abstract
This paper deals with a learning method for digit character recognition.
We propose to expand character image databases, by automatically
generating deformations, noises and new fonts, and then to use a simple
classifier based on k nearest neighbor technique.
The results of first experiments show that the classifier is more robust
on the resulting larger database.
Moreover, performance on the MNIST digit character database is very
promising.
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