应用变归一化距离公式对古兰经图像进行分类

Al Khowarizmi, Akhm, M. Lubis, Arif Ridho Lubis
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引用次数: 11

摘要

古兰经是一本穆斯林圣书,最初是用阿拉伯语写成的,阅读它的方式应该与启示时代的使者和同伴的发音和拼写保持一致。遵循其诵读规律,避免对经文的误读是非常重要的,利用人工神经网络和图像处理的存在,可以将各种类型的《塔伊weed》划分为《古兰经》的诵读纪律,从而在读音和解读方面为读者提供支持。在此分类中,古兰经背诵以若干归一化距离公式的形式,以获得分类的正确优化,即归一化曼哈顿距离,该距离在<0.5时是一致的,而在Tajweed古兰经的情况下没有应用的归一化汉明距离,因为生成的值为1。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Tajweed Al-Qur'an on Images Applied Varying Normalized Distance Formulas
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.
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