A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals

  • Authors:
  • Y. S. Huang;C. Y. Suen

  • Affiliations:
  • -;-

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 1995

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Abstract

For pattern recognition, when a single classifier cannot provide a decision which is 100 percent correct, multiple classifiers should be able to achieve higher accuracy. This is because group decisions are generally better than any individual驴s. Based on this concept, a method called the 驴Behavior-Knowledge Space Method驴 was developed, which can aggregate the decisions obtained from individual classifiers and derive the best final decisions from the statistical point of view. Experiments on 46,451 samples of unconstrained handwritten numerals have shown that this method achieves very promising performances and outperforms voting, Bayesian, and Dempster-Shafer approaches.