Off-line Arabic hand-writingrecognition using artificial neural networkwith genetics algorithm

Abstract EN

Artificial Neural Networks (ANN) were used in the recognition of the printed Arabic text with a high rate of success.

In contrast, Arabic hand-writing recognition has many challenges,some were tackled in some research recently.

In this paper we used ANN in recognizingArabic hand-written characterswith the Genetics Algorithm (GA).

The GA was used to search for the best ANN structure.

We consider Arabic off-line characters represented by a series of (x,y) coordinates.

The dataset was gathered from a couple of volunteers, used the E-pen to write different Arabic letters.

AMATLAB program was implemented to store the written characters and extractstheir features.

Features were determined based on the shape and number of segments that made up the characters.

The recognition results were very promising when using ANN with the GA in comparison with other relevant approaches.

On average more than 95% of accuracy was achieved whenGA is used to adjust ANN structure in order to get the best recognition rate