A Brief Review of Classifiers used in OCR Applications

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-34 Number-2
Year of Publication : 2016
Authors : Satish Kumar
DOI :  10.14445/22312803/IJCTT-V34P114

MLA

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.