Paper Title:
Handwritten Character Recognition Research Based on Adaptive Minimum Distance Classifiers Integration
  Abstract

It is difficulty to gain completely satisfactory effect if a single classification is used to check a complicated recognition classification problem. Using the complementarities between the different classify method, integrating many classifiers, it can reduce the identification mistake and strengthen recognition robustness. Taking a offline handwritten number recognition system as an example, adopting Bayesian discriminate function based on minimal mistake rate, uniting recognition algorithm of RBF kernel function, using Bagging technology, adaptive minimum distance classifiers integration is designed in which there is minimal mistake rate. Furthermore, an offline handwritten number recognition system in high accuracy is exploited in which there is adaptive and self-learning function. It can be used for important economic fields such as financial statement and bank paper.

  Info
Periodical
Edited by
Ran Chen
Pages
3388-3392
DOI
10.4028/www.scientific.net/AMM.44-47.3388
Citation
Z. P. Tang, J. P. Sun, L. S. Zhong, "Handwritten Character Recognition Research Based on Adaptive Minimum Distance Classifiers Integration", Applied Mechanics and Materials, Vols. 44-47, pp. 3388-3392, 2011
Online since
December 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Yan Wang, Xiu Xia Wang, Sheng Lai
Abstract:In ensemble learning, in order to improve the performance of individual classifiers and the diversity of classifiers, from the classifiers...
55
Authors: Jian Ping Wang, Ke Qiong Chen, Jin Ling Wang, Cheng Hui Zhu
Chapter 10: Manufacturing Process Planning and Scheduling
Abstract:The decision information system of off-line handwritten Chinese character recognition based on variable precision rough set is constructed in...
1715
Authors: Yu Long Xu, Yong Mei Zhang
Chapter 5: Information Processing and Computational Science
Abstract:In this paper, a recognition method for multiple classifiers is proposed, which combines an improved eigenface method with Support Vector...
1075
Authors: Chien Chih Wang
Chapter 10: Mechatronics and Control Technology
Abstract:To improve the printed circuit board (PCB) manufacturing process, it is important to have an automatic inspection system that classifies...
1393
Authors: Ru Zhang
Chapter 6: Data Acquisition and Data Processing, Computational Techniques
Abstract:With the ceramics market's developing, the use of image processing and intelligent algorithm is applied to the ancient ceramics recognition...
1201