This paper addresses the problem of to what extent linear transformation can alleviate nonlinear distortion. We investigate a technique of global affine transformation (GAT) correlation to absorb linear distortion between gray-scale images. Features used in GAT correlation are occurrence probabilities of black pixels or gradients. Experiments using the handwritten numeral database IPTP CDROM1B show that the entropy of GAT-superimposed images decreases by around 15%. Furthermore, gray-level-based GAT correlation improves the recognition rate from 85.78% to 91.01%, while gradient-based GAT correlation improves the recognition rate from 91.80% to 94.02%. These results show that GAT correlation has a marked effect of improving both shape matching and discrimination abilities by extracting linear distortion from nonlinear one.
Shape matching using GAT correlation against nonlinear distortion and its application to handwritten numeral recognition
2003-01-01
358948 byte
Conference paper
Electronic Resource
English
British Library Conference Proceedings | 2003
|Script Independent Handwritten Numeral Recognition
British Library Conference Proceedings | 2006
|British Library Conference Proceedings | 2003
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