首页 | 本学科首页   官方微博 | 高级检索  
     


An SVD audio watermarking approach using chaotic encrypted images
Authors:Waleed Al-Nuaimy  Mohsen AM El-Bendary  Amira Shafik  Farid Shawki  AE Abou-El-azm  NA El-Fishawy  Said M Elhalafawy  Salaheldin M Diab  Bassiouny M Sallam  Fathi E Abd El-Samie  HB Kazemian[Author vitae]
Affiliation:aDepartment of Electrical Engineering and Electronics, University of Liverpool, UK;bDepartment of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt;cIntelligent Systems Research Centre, Faculty of Computing, London Metropolitan University, UK
Abstract:This paper presents a new approach for audio watermarking using the Singular Value Decomposition (SVD) mathematical technique. The proposed approach can be used for data hiding in the audio signals transmitted over wireless networks and for multi-level security systems as will be stated in the applications section. This approach is based on embedding a chaotic encrypted watermark in the singular values of the audio signal after transforming it into a 2-D format. The selection of the chaotic encryption algorithm for watermark encryption is attributed to its permutation nature, which resists noise, filtering, and compression attacks. After watermark embedding, the audio signal is transformed again into a 1-D format. The transformation between the 1-D and 2-D formats is performed in the well-known lexicographic ordering method used in image processing. The proposed approach can be implemented on the audio signal as a whole or on a segment-by-segment basis. The segment-by-segment implementation allows embedding the same watermark several times in the audio signal, which enhances the detectability of the watermark in the presence of severe attacks. Experimental results show that the proposed audio watermarking approach maintains the high quality of the audio signal and that the watermark extraction and decryption are possible even in the presence of attacks.
Keywords:Audio watermarking  SVD  Copyright protection
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号