Decision fusion and reliability control in handwritten digit recognition system
Journal
Journal of computing and information technology
Date Issued
2002-12-30
Author(s)
Gjorgjevikj, Dejan
Younes Bennani,
Chakmakov, Dushan
Radevski, Vladimir
Abstract
In this paper, the cooperation of two feature families
for handwritten digit recognition using a committee
of Neural Network NN classifiers will be examined.
Various cooperation schemes will be investigated and
corresponding results will be presented. To improve the
system reliability, we will upgrade the committee scheme
using multistage classification based on rule-based and
statistical cooperation. The rule-based cooperation enables an easy and efficient implementation of various
rejection criteria while the statistical cooperation offers
better possibility for fine-tuning of the recognition versus
the reliability tradeoff. The final system has been
implemented using rule-based reasoning with rejection
criteria for classifier decision fusion and the generalized
committee cooperation scheme for classification of the
rejected digit patterns. The presented results show
that we propose a successful approach for reliability
control in committee classifier environment and indicate
that a suitable cooperation of statistical and rule-based
decision fusion is a promising approach in handwritten
recognition systems.
for handwritten digit recognition using a committee
of Neural Network NN classifiers will be examined.
Various cooperation schemes will be investigated and
corresponding results will be presented. To improve the
system reliability, we will upgrade the committee scheme
using multistage classification based on rule-based and
statistical cooperation. The rule-based cooperation enables an easy and efficient implementation of various
rejection criteria while the statistical cooperation offers
better possibility for fine-tuning of the recognition versus
the reliability tradeoff. The final system has been
implemented using rule-based reasoning with rejection
criteria for classifier decision fusion and the generalized
committee cooperation scheme for classification of the
rejected digit patterns. The presented results show
that we propose a successful approach for reliability
control in committee classifier environment and indicate
that a suitable cooperation of statistical and rule-based
decision fusion is a promising approach in handwritten
recognition systems.
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