A variation and distortion tolerant structural pre-classifier for hierarchical character recognition

Author

Khan, Nadeem A. ; Hegt, Hans A. ; Allue, Ignacio C.

Author_Institution

Dept. of Electr. Eng., Eindhoven Univ. of Technol., Netherlands

Volume

5

fYear

1998

fDate

11-14 Oct 1998

Firstpage

4264

Abstract

This paper presents a structural pre-classification approach to reduce the number of class models to be compared with a given sample during the main classification stage. This helps to increase the overall classification speed and to improve the recognition accuracy. The approach is based on preparing high-level coarse shape models of character classes permitting similar character-classes to merge into super-groups. The approach is robust to distortion and font or writing style variations

Keywords

character recognition; hierarchical systems; image classification; character-classes; classification speed; distortion tolerant structural pre-classifier; font variations; hierarchical character recognition; high-level coarse shape models; super-groups; variation tolerant structural pre-classifier; writing style variations; Acceleration; Character recognition; Convergence; Electronic mail; Impedance matching; Neural networks; Prototypes; Robustness; Shape; Writing;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on

Conference_Location

San Diego, CA

ISSN

1062-922X

Print_ISBN

0-7803-4778-1

Type

conf

DOI

10.1109/ICSMC.1998.727515

Filename

727515