Shape Matching Using GAT Correlation against Nonlinear Distortion and its Application to Handwritten Numeral Recognition

Authors:
Toru Wakahara
Affiliations:
-
Venue:
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Year:
2003

Citing 6
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Abstract

This paper addresses the problem of to what extentlinear transformation can alleviate nonlinear distortion.We investigate a technique of global affinetransformation (GAT) correlation to absorb lineardistortion between gray-scale images. Features used inGAT correlation are occurrence probabilities of blackpixels or gradients. Experiments using the handwrittennumeral database IPTP CDROM1B show that theentropy of GAT-superimposed images decreases byaround 15%. Furthermore, gray-level-based GATcorrelation improves the recognition rate from 85.78% to91.01%, while gradient-based GAT correlation improvesthe recognition rate from 91.80% to 94.02%. Theseresults show that GAT correlation has a marked effect ofimproving both shape matching and discriminationabilities by extracting linear distortion from nonlinearone.