A new embedding technique based on psychovisual threshold for robust and secure compressed video steganography

Ferda, Ernawan and Muhammad Fuad, Abdullah (2020) A new embedding technique based on psychovisual threshold for robust and secure compressed video steganography. In: 33rd General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2020 , 29 August - 05 September 2020 , Rome, Italy. pp. 1-5. (9231989). ISSN 2642-4339 ISBN 978-946396800-3

	Pdf 09231989.pdf Restricted to Repository staff only Download (108kB) | Request a copy
Preview	Pdf A new embedding technique based on psychovisual threshold for robust .pdf Download (156kB) | Preview

Abstract

Videos are often compressed to reduce storage and transmission payload at the expense of lower quality due to bandwidth-related issues. Most video steganography techniques do not provide robustness against compression technique. Thus, it is vital to develop a steganography technique that can be resistant against compression. This research proposed a new embedding technique in video steganography based on object motion and modified entropy. The object motions in the video frame were determined by horizontal and vertical motion vectors. The video frames that had object motion were computed by modified entropy. The proposed scheme embedded data along with the object motion by modifying Discrete Cosine Transform (DCT) coefficients in the video frames. Six DCT coefficients were selected in the middle frequency using DCT-psychovisual effects of hiding messages. The experimental results showed that the scheme achieved good robustness of message recovery in terms of Bit Error Rate (BER) and Normalised CrossCorrelation (NC). The recovered message of the proposed steganography scheme can survive video compression,

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Discrete cosine transforms; Entropy; Video compression; Transforms; Transform coding; Robustness; Distortion
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division:	Institute of Postgraduate Studies
Depositing User:	Dr. Ferda Ernawan
Date Deposited:	16 Aug 2023 04:58
Last Modified:	16 Aug 2023 04:58
URI:	http://umpir.ump.edu.my/id/eprint/30071
Download Statistic:	View Download Statistics

Actions (login required)

View Item