A Brief Review of Classifiers used in OCR Applications
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2016 by IJCTT Journal | ||
| Volume-34 Number-2 |
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| Year of Publication : 2016 | ||
| Authors : Satish Kumar | ||
| DOI : 10.14445/22312803/IJCTT-V34P114 |
Satish Kumar "A Brief Review of Classifiers used in OCR Applications". International Journal of Computer Trends and Technology (IJCTT) V34(2):80-88, April 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
The performance of a recognition
system depends upon the classifiers used for
classification purpose. Powerful is the
discrimination ability of a classifier, better is its
recognition performance. The generalization ability
of a classifier is measured on the basis of its
performance in classifying the test patterns. There
are various factors which affect generalization.
Moreover, the feature extraction method(s) used for
training a classifier also affects the performance of a
classifier. In this paper, a brief theoretical review of
various classifiers is made. The various characters
of each are covered. The classifiers covered are
Bayes, Parzen, probabilistic, polynomial,
discriminant, radial basis networks, multi layer
perceptron(MLP), k-NN, SVM and SOM.
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Keywords
Classifiers, Recognition, PNN, SOM,
k-NN, SVM, MLP.