Automatic recognition of text on scanned images has enabled many applications such as searching for words in large volumes of documents, automatic sorting of postal mail, and convenient editing of previously printed documents. The domain of handwriting in the Arabic script presents unique technical challenges and has been addressed more recently than other domains. Many different methods have been proposed and applied to various types of images. Here we will focus on the recognition part of handwritten Arabic letters, including the unlimited variation in human handwriting and the large public databases.

In this project we built a model which can classify a new image to an arabic characters with an accuracy of 97.1% when testing on more than 3360 different images.

Link of the dataset that was used

AlaZebdeh
MonebKhaled