A Blind Video Copyright Protection Technique in Maximum and Minimum Energy Frames Based on The Fast Walsh Hadamard Transform (FWHT) and Discrete Wavelet Transform (DWT) and Arnold Map
Dublin Core
Title
A Blind Video Copyright Protection Technique in Maximum and Minimum Energy Frames Based on The Fast Walsh Hadamard Transform (FWHT) and Discrete Wavelet Transform (DWT) and Arnold Map
Subject
Fast Walsh Hadamard Transform (FWHT), Discrete Wavelet Transform (DWT), Arnold Map
Description
Video copyright protection is the most generally acknowledged method of preventing data piracy. This paper proposes a blind video copyright protection technique based on the Fast Walsh Hadamard Transform (FWHT), Discrete Wavelet Transform (DWT), and Arnold Map. The proposed method chooses only frames with maximum and minimum energy features to host the watermark. It also exploits the advantages of both the fast Walsh Hadamard transform (FWHT) and discrete wavelet transforms (DWT) for watermark embedding. The Arnold map encrypts watermarks before the embedding process and decrypts watermarks after extraction. The results show that the proposed method can achieve a fast embedding time, good transparency, and robustness against various attacks.
Creator
Resen, Mohammed S.
Laftah, Muna M.
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 10 (2022); pp. 163-175
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2022-05-24
Rights
Copyright (c) 2022 Haider Th.Salim Alrikabi; Mohammed S. Resen, Muna M. Laftah
https://creativecommons.org/licenses/by/4.0
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Mohammed Resen S. and Muna Laftah M., A Blind Video Copyright Protection Technique in Maximum and Minimum Energy Frames Based on The Fast Walsh Hadamard Transform (FWHT) and Discrete Wavelet Transform (DWT) and Arnold Map, International Association of Online Engineering (IAOE), Vienna, Austria, 2022, accessed November 23, 2024, https://igi.indrastra.com/items/show/2249