Off-Line Handwritten Chinese Character Recognition with Nonlinear Pre-classification

Authors:
Lixin Zhen;Ruiwei Dai
Affiliations:
-;-
Venue:
ICMI '00 Proceedings of the Third International Conference on Advances in Multimodal Interfaces
Year:
2000

Citing 3
Cited 1

Clustering of clusters

Pattern Recognition
Offline Recognition of Chinese Handwriting by Multifeature and Multilevel Classification

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Handwritten Character Recognition System Using Directional Element Feature and Asymmetric Mahalanobis Distance

IEEE Transactions on Pattern Analysis and Machine Intelligence

Recognition-based digitalization of korean historical archives

AIRS'04 Proceedings of the 2004 international conference on Asian Information Retrieval Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we describe a new Chinese character recognition system, in which neural networks are employed as a nonlinear pre-classifier to pre-classify similar Chinese characters, and an algorithm of clustering called Association Class Grouping algorithm (ACG) is hired to cluster similar Chinese characters. In our system, feature of contour direction is extracted to form a Bayesian classifier. Experiments have been conducted to recognize 3,755 Chinese Characters. The recognition rate is about 92%.