Payload Capacity Scheme for Quran Text Watermarking Based on Vowels with Kashida

Journal article (2021)

Authors

Ali A.R. Alkhafaji Malaysia University of Technology
Nilam Nur Amir Sjarif Malaysia University of Technology
M.A Shahidan Malaysia University of Technology
Nurulhuda Firdaus Mohd Azmi Malaysia University of Technology
Haslina Md Sarkan Malaysia University of Technology
Suriayati Chuprat Malaysia University of Technology
Osamah Ibrahim Khalaf Al-Nahrain University
Copyright: © 2021 Ali A.R. Alkhafaji, Nilam Nur Amir Sjarif, M.A Shahidan, Nurulhuda Firdaus Mohd Azmi, Haslina Md Sarkan, Suriayati Chuprat, Osamah Ibrahim Khalaf, Ehab Nabiel Al-Khanak
DOI: https://doi.org/10.32604/cmc.2021.015803
More Info
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Published Date

2021

Language

English

Abstract

The most sensitive Arabic text available online is the digital Holy Quran. This sacred Islamic religious book is recited by all Muslims worldwide including non-Arabs as part of their worship needs. Thus, it should be protected from any kind of tampering to keep its invaluable meaning intact. Different characteristics of Arabic letters like the vowels (), Kashida (extended letters), and other symbols in the Holy Quran must be secured from alterations. The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR) and Embedding Ratio (ER). A watermarking technique with enhanced attributes must, therefore, be designed for the Quran’s text using Arabic vowels with kashida. The gap addressed by this paper is to improve the security of Arabic text in the Holy Quran by using vowels with kashida. The purpose of this paper is to enhance the Quran text watermarking scheme based on a reversing technique. The methodology consists of four phases: The first phase is a pre-processing followed by the second phase-the embedding process phase—which will hide the data after the vowels. That is, if the secret bit is “1”, then the kashida is inserted; however, the kashida is not inserted if the bit is “0”. The third phase is the extraction process and the last phase is to evaluate the performance of the proposed scheme by using PSNR (for the imperceptibility) and ER (for the capacity). The experimental results show that the proposed method of imperceptibility insertion is also optimized with the help of a reversing algorithm. The proposed strategy obtains a 90.5% capacity. Furthermore, the proposed algorithm attained 66.1% which is referred to as imperceptibility.