Chinese Character Recognition - Comparison of Classification Methodologies

Authors:
Sameer Singh;Adnan Amin;K. C. Sum
Affiliations:
-;-;-
Venue:
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Year:
2002

Citing 13
Cited 0

Fuzzy mathematical approach to pattern recognition

Fuzzy mathematical approach to pattern recognition
Separating similar complex Chinese characters by Walsh transform

Pattern Recognition
Recognition of Handwritten Chinese Characters by Modified Hough Transform Techniques

IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Detection of Dominant Points on Digital Curves

IEEE Transactions on Pattern Analysis and Machine Intelligence
Stroke segmentation by Bernstein-Be´zier curve fitting

Pattern Recognition
A transformation invariant matching algorithm for handwritten Chinese character recognition

Pattern Recognition
Handwritten character recognition using a 2-layer random graph model by relaxation matching

Pattern Recognition
Character recognition by stochastic sectionalgram approach

Pattern Recognition
On speeding candidate selection in handprinted Chinese character recognition

Pattern Recognition
One-Pass Parallel Thinning: Analysis, Properties, and Quantitative Evaluation

IEEE Transactions on Pattern Analysis and Machine Intelligence
C4.5: programs for machine learning

C4.5: programs for machine learning
Attributed String Matching by Split-and-Merge for On-Line Chinese Character Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Angle Detection on Digital Curves

IEEE Transactions on Computers

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we propose the use of dominant point method for Chinese character recognition. We compare the performance of three classifiers on the same inputs; a statistical linear classifier, a machine learning C4.5 classifier, and a fuzzy nearest neighbour method of classification. Such a comparison highlights the degree of advantage of correct recognition method for our problem.