%0 Journal Article
	%A Reza Ebrahimpour and  Samaneh Hamedi
	%D 2009
	%J International Journal of Electrical and Computer Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 33, 2009
	%T Hand Written Digit Recognition by Multiple Classifier Fusion based on Decision Templates Approach
	%U https://publications.waset.org/pdf/7930
	%V 33
	%X Classifier fusion may generate more accurate
classification than each of the basic classifiers. Fusion is often based
on fixed combination rules like the product, average etc. This paper
presents decision templates as classifier fusion method for the
recognition of the handwritten English and Farsi numerals (1-9).
The process involves extracting a feature vector on well-known
image databases. The extracted feature vector is fed to multiple
classifier fusion. A set of experiments were conducted to compare
decision templates (DTs) with some combination rules. Results from
decision templates conclude 97.99% and 97.28% for Farsi and
English handwritten digits.
	%P 1715 - 1720