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

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

• Type: Conference
• Year: 2003
• Where: ICDAR
• Authors: Toru Wakahara
• Keywords: Document Analysis, Extent Linear Transformation, GAT Correlation, Gray-level-based Gat Correlation, ICDAR 2003