Propose Recognition Technique Model for Arabic Islamic Manuscripts

This paper presents a new method for Ancient Islamic Manuscripts Recognition and Arabic scrip recognition. The main contributions of this work is that the method of recognition and classification of the data used multilayer model of neural network, used as a technique Arabic Manuscript, the performance of the proposed method is assessed using samples extracted from a historical handwritten manuscript. Arabic text is cursive, and each character may have up to four different shapes based on its location in a word. Quite often old documents are subject to background damage. Examples of background damages are varying contrast, smudges, dirty background, and ink through page, outdated paper and uneven background, The hyper plane approach is employed as classifiers due to the low computation overhead during training and recall process.

Keywords: Recognition Technique, Arabic Manuscripts, Optimal hyperplane, Support vectors, Margin, Origin.