There is existing research on document identification.

With increasing digital documents on the internet, it is important to identify that the document is genuine or not. Twelve features are extracted from the formed triangles used.ĭocument identification is used to extract information from a digital document such as Al-Quran, articles, agreement and so on. The number of model is 711 for the UML and 1019 for the SML. Hence, the model and test data are Arabic calligraphy letters taken from calligraphy books. This stage focuses on the accuracy of Arabic calligraphy classification. Experiments have been conducted using seven Unsupervised Machine Learning (UML) algorithms and one Supervised Machine Learning (SML). The features are extracted from the triangle to represent the Jawi (Arabic writing in Malay language) characters. This technique defines three important coordinates in the image of each character and translates it into triangle geometry form. For Digital Jawi Paleography, a novel technique is proposed based on the triangle. Information that are used are features from characters, tangent value and features known as Grey-Level Co-occurrence Matrix (GLCM). Researches on digital paleography using calligraphy are done on the manuscripts to identify unidentified place of origin, number of writers, and the date of ancient manuscripts. Calligraphy classification of the ancient manuscripts gives useful information to paleographers.

Tulisan jawi khat software