TY  - JOUR
T1  - A New off Line System for Handwritten Digits Recognition
AU - , Salim Ouchtati AU - , Mohamed Redjimi AU - , Mouldi Bedda AU - , Faouzi Bouchareb 
JO  - Asian Journal of Information Technology
VL  - 5
IS  - 6
SP  - 620
EP  - 626
PY  - 2006
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2006.620.626
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2006.620.626
KW  - Optical characters recognition
KW  -neural networks
KW  -barr features
KW  -image processing
KW  -pattern recognition
AB  - In this study, we present an off line method of handwritten isolated digits Recognition. The study
is based on the analysis and the evaluation of multi-layers perceptron performances, trained with the gradient
back propagation algorithm. It is hoped that the results of the evaluation contribute to the conception of
operational systems. The used parameters to form the input vector of the neural network are extracted on the
binary images of the digits by two methods: the centred moments of the distribution sequences and the Barr
features
ER  -