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2008
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Handwritten Chinese character recognition using Local Discriminant Projection with Prior Information

11 years 4 months ago
Handwritten Chinese character recognition using Local Discriminant Projection with Prior Information
In this paper, we propose a new method to model the manifold of handwritten Chinese characters using the local discriminant projection. We utilize a cascade framework that combines global similarity with local discriminative cues to recognize Chinese characters. We find the similarity of different characters using a nearest-neighbor (NN) classifier, and followed by the Local Discriminant Projection with Prior Information (LDPPI) to map similar characters within a cluster to a low-dimensional space. We evaluate the proposed method on two large public datasets, ETL9B which contains 607,200 handwritten characters from 200 people, and HCL2000 which contains 3,755,000 characters written by 1,000 people. The experimental results demonstrate that the proposed method achieves 0.74%
Honggang Zhang, Jie Yang, Jun Guo, Weihong Deng
Added 05 Nov 2009
Updated 06 Nov 2009
Type Conference
Year 2008
Where ICPR
Authors Honggang Zhang, Jie Yang, Jun Guo, Weihong Deng
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