An off Line System for the Handwritten Numeric Chains Recognition
In this syudy we present an off line system for the recognition of the handwritten numeric chains. Our study is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. 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 distributions sequences and the Barr features. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.