Classification of Tajweed Al-Qur'an on Images Applied Varying Normalized Distance Formulas

Abstract

Al-Qur'an is a Muslim holy book which is written originally in Arabic where the way of reading it should be aligned with the pronunciation and spelling of the messenger and companion in the time of revelation. It is very important to follow the rule of its reading to avoid misinterpretation of the verses, which the existence of artificial neural networks and image processing can be used to classify various type of Tajweed as the reading discipline of Al-Quran in order to support the readers in term of pronunciation and interpretation. In this classification, the recitation of Al-Qur'an in the form of a number of normalized distance formulas in order to obtain the right optimization for the classification namely normalized Manhattan distance which is consistent at a value <0.5 and one that is not applied in the case of Tajweed Al-Qur'an is normalized hamming distance because the value generated is 1.