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Research on Human and Machine Performance of Handwritten Chinese Character Recognition in HCL2000
Wan Xinxin * #,Zhang Honggang
School of Information and Communications Engineering, Beijing University of Posts and Telecommunications
*Correspondence author
#Submitted by
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Funding: none
Opened online: 9 December 2010
Accepted by: none
Citation: Wan Xinxin,Zhang Honggang.Research on Human and Machine Performance of Handwritten Chinese Character Recognition in HCL2000[OL]. [ 9 December 2010] http://en.paper.edu.cn/en_releasepaper/content/4394583
 
 
In this paper, human performance on handwritten Chinese character recognition is compared to machine, which aims to obtain the required accuracy for further handwritten word segmentation and recognition. HCL2000, one of the largest databases of handwritten Chinese characters, introduces sample characters into the performance evaluation. A system of Human Performance Test on HCL2000 is designed to examine the accuracy of human recognition. According to the experiment results, the best machine record is competitive with average human performance. LPP and MFA employing the gradient feature vectors of size 512 far outperform LDA on the same dimensionality.
Keywords:Pattern Recognition; HCL2000; Handwritten Chinese Character Recognition; Human/Machine Performance; Gradient Feature
 
 
 

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