Title :
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
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4778-1
DOI :
10.1109/ICSMC.1998.727515
