A Survey of Elastic Matching Techniques for Handwritten Character Recognition

Authors:
Seiichi Uchida;Hiroaki Sakoe
Affiliations:
The authors are with the Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka-shi, 812--8581 Japan. E-mail: uchida@is.kyushu-u.ac.jp;The authors are with the Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka-shi, 812--8581 Japan. E-mail: uchida@is.kyushu-u.ac.jp
Venue:
IEICE - Transactions on Information and Systems
Year:
2005

Citing 0
Cited 5

Deformation Models for Image Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Mosaicing-by-recognition for video-based text recognition

Pattern Recognition
Deformation-Aware Log-Linear Models

Proceedings of the 31st DAGM Symposium on Pattern Recognition
Logical DP matching for detecting similar subsequence

ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
k-NN classification of handwritten characters via accelerated GAT correlation

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a survey of elastic matching (EM) techniques employed in handwritten character recognition. EM is often called deformable template, flexible matching, or nonlinear template matching, and defined as the optimization problem of two-dimensional warping (2DW) which specifies the pixel-to-pixel correspondence between two subjected character image patterns. The pattern distance evaluated under optimized 2DW is invariant to a certain range of geometric deformations. Thus, by using the EM distance as a discriminant function, recognition systems robust to the deformations of handwritten characters can be realized. In this paper, EM techniques are classified according to the type of 2DW and the properties of each class are outlined. Several topics around EM, such as the category-dependent deformation tendency of handwritten characters, are also discussed.