Abstract
o raise the reliability, a hybrid multiple classifier system is proposed by integrating the cooperation and combination of three classifiers: SVM [1], MQDF [3], and leNet5 [2]. In combination, we apply the total probability theorem to the classifiers at the rank level. Meanwhile, differential measurement and probability measurement are defined for the rejection option on different types of classifiers. Considerable improvement has been observed, and the final recognition rate of this system ranges from 95.54 to 99.11% with a reliability of 99.54 to 99.11%.
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Chun Lei He received an MS and BS degree in applied mathematics from Jilin University, China, in 2000 and 1998, respectively. Currently, she is a research assistant and graduate student at the Center for Pattern Recognition and Machine Intelligence (CENPARMI) at Concordia University, Canada. Her research interest is handwriting recognition using expert systems techniques.
Ching Y. Suen received an MS degree in engineering from the University of Hong Kong and a PhD degree from the University of British Columbia, Canada. In 1972, he joined the Department of Computer Science of Concordia University, where he became a professor in 1979 and served as chairman from 1980 to 1984 and as associate dean for research of the Faculty of Engineering and Computer Science from 1993 to 1997. He has guided/hosted 65 visiting scientists and professors and supervised 60 doctoral and master’s graduates. Currently he holds the distinguished Concordia Research Chair in Artificial Intelligence and Pattern Recognition, and is the director of CENPARMI, the center for PR and MI.
Prof. Suen is the author/editor of 11 books and more than 400 papers on subjects ranging from computer vision and handwriting recognition to expert systems and computational linguistics. A Google search of “Ching Y. Suen” will show some of his publications. He is the founder of The International Journal of Computer Processing of Oriental Languages and served as its first editor-in-chief for 10 years. Presently he is an associate editor of several journals related to pattern recognition.
A fellow of the IEEE, IAPR, and the Academy of Sciences of the Royal Society of Canada, he has served several professional societies as president, vice-president, or governor. He is also the founder and chair of several conference series including ICDAR, IWFHR, and VI. He had been the general chair of numerous international conferences, including the International Conference on Computer Processing of Chinese and Oriental Languages in August 1988 held in Toronto, International Conference on Document Analysis and Recognition held in Montreal in August 1995, and the International Conference on Pattern Recognition held in Quebec City in August 2002.
Dr. Suen has given 150 seminars at major computer industries and various government and academic institutions around the world. He has been the principal investigator of 25 industrial/government research contracts and is a grant holder and recipient of prestigious awards, including an ITAC/NSERC cash + grant award from the Information Technology Association of Canada and the Natural Sciences and Engineering Research Council of Canada in 1992 and the Concordia “Research Fellow” award in 1998.
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He, C.L., Suen, C.Y. A hybrid multiple classifier system of unconstrained handwritten numeral recognition. Pattern Recognit. Image Anal. 17, 608–611 (2007). https://doi.org/10.1134/S1054661807040219
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DOI: https://doi.org/10.1134/S1054661807040219