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Jian-Huang Lai

Work place: School of Information Science and Technology, Sun Yat-sen University, Guangzhou, P. R. China

E-mail: stsljh@mail.sysu.edu.cn

Website:

Research Interests: Pattern Recognition, Image Compression, Image Manipulation, Image Processing, Multimedia Information System

Biography

Jian-Huang Lai received his M.Sc. degree in applied mathematics in 1989 and his Ph.D. in mathematics in 1999 from SUN YAT-SEN University, P. R. China.
He joined Sun Yat-sen University in 1989 as an Assistant Professor, where currently, he is a Professor with the Department of Automation of School of Information Science and Technology and vice dean of School of Information Science and Technology.
Prof. Lai had successfully organized the International Conference on Advances in Biometric Personal Authentication'2004, which was also the Fifth Chinese Conference on Biometric Recognition (Sinobiometrics'04), Guangzhou, in December 2004. He has taken charge of more than five research projects, including NSF-Guangdong (No.U0835005), NSFC (NO.60144001, 60373082, 60675016), the Key (Keygrant) Project of Chinese Ministry of Education (No.105134), and NSF of Guangdong, China (No.021766, 06023194). He has published over 80 scientific papers in the international journals and conferences on image processing and pattern recognition. His current research interests are in the areas of digital image processing, pattern recognition, multimedia communication, wavelet and its applications.

Prof. Lai serves as a standing member of the Image and Graphics Association of China and also serves as a standing director of the Image and Graphics Association of Guangdong.

Author Articles
A Stroke Shape and Structure Based Approach for Off-line Chinese Handwriting Identification

By Jun Tan Jian-Huang Lai Chang-Dong Wang Ming-Shuai Feng

DOI: https://doi.org/10.5815/ijisa.2011.02.01, Pub. Date: 8 Mar. 2011

Handwriting identification is a technique of automatic person identification based on the personal handwriting. It is a hot research topic in the field of pattern recognition due to its indispensible role in the biometric individual identification. Although many approaches have emerged, recent research has shown that off-line Chinese handwriting identification remains a challenge problem. In this paper, we propose a novel method for off-line Chinese handwriting identification based on stroke shapes and structures. To extract the features embedded in Chinese handwriting characters, two special structures have been explored according to the trait of Chinese handwriting characters. These two structures are the bounding rectangle and the TBLR quadrilateral. Sixteen features are extracted from the two structures, which are used to compute the unadjusted similarity, and the other four commonly used features are also computed to adjust the similarity adaptively. The final identification is performed on the similarity. Experimental results on the SYSU and HanjaDB1 databases have validated the effectiveness of the proposed method.

[...] Read more.
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