A new shape transformation approach to handwritten character recognition

A new simple algorithm, based on dynamic programming is presented, for handwritten character recognition, with improved accuracy. The proposed shape transform (ST) approach is based on the calculation of the cost of transforming the image of a given character into that of another, thus taking into a...

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Bibliographic Details
Published inObject recognition supported by user interaction for service robots Vol. 1; pp. 584 - 587 vol.1
Main Authors Liolios, N., Kavallieratou, E., Fakotakis, N., Kokkinakis, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Character recognition
Concurrent computing
Costs
Dynamic programming
Heuristic algorithms
Image databases
Karhunen-Loeve transforms
NIST
Shape
Spatial databases
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Summary:A new simple algorithm, based on dynamic programming is presented, for handwritten character recognition, with improved accuracy. The proposed shape transform (ST) approach is based on the calculation of the cost of transforming the image of a given character into that of another, thus taking into account local geometrical similarities and differences. A large experiment is conducted on the NIST database, and the effectiveness of the proposed method is compared to the Karhunen Loeve transform method, with which a similar experiment was contacted reporting the best results in the literature. The experiments performed show that this new approach leads to improved recognition. It is more demanding in computer time, which is becoming ever more plentiful, but it lends itself to very efficient parallel hardware implementation.
ISBN:076951695X
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2002.1044808