A Blind DWT-SCHUR Based Digital Video Watermarking Technique

Rajab, Lama; Al-Khatib, Tahani; Al-Haj, Ali

doi:10.4236/jsea.2015.84023

Cited by 27 publications

(13 citation statements)

References 12 publications

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“…The proposed technique showed high efficiency due to the use of Schur decomposition which requires fewer computations compared to other transforms. The imperceptibility of the scheme was also very high due to the use of DWT transform; therefore, no visual distortion was noticed in the watermarked video after embedding [8]. Even though such approaches are very effective damage to the image to certain extent can make them very difficult for extraction [8].…”

Section: Fig 1: the Embedding Of Watermark Bitsmentioning

confidence: 96%

“…The imperceptibility of the scheme was also very high due to the use of DWT transform; therefore, no visual distortion was noticed in the watermarked video after embedding [8]. Even though such approaches are very effective damage to the image to certain extent can make them very difficult for extraction [8]. In the work of Gaj, Sibaji, Ashish Singh Patel, and Arijit Sur et al, a compressed domain video watermarking scheme was proposed which embeds the watermark in the homogeneous moving object within a shot of video sequence to resist geometric attacks such as rotation, scaling etc.…”

Section: Fig 1: the Embedding Of Watermark Bitsmentioning

confidence: 99%

See 1 more Smart Citation

Security of Surveillance Wireless Camera Sensor Network Systems using Embedding Techniques for Authentication

Kester¹,

Asisat²,

Chibueze³

2015

IJCA

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Security in today's wireless camera sensor networks is very crucial for authentication of video feeds from appropriate sources. This will ensure the safety and security of the digital video feeds as well as provide means of authenticating the video. These authentication approaches should be able to identify tamper detection. In this paper, we propose an embedding technique for authentication of video feeds obtained from wireless camera sensor networks. These approaches are able make the signals more secured and easily verifiable. General TermsDigital signal processing, image processing, security, multimedia, sensor networks.

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Section: Fig 1: the Embedding Of Watermark Bitsmentioning

confidence: 96%

Section: Fig 1: the Embedding Of Watermark Bitsmentioning

confidence: 99%

Security of Surveillance Wireless Camera Sensor Network Systems using Embedding Techniques for Authentication

Kester¹,

Asisat²,

Chibueze³

2015

IJCA

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“…SVD is a powerful mathematical tool used to analyze the matrix. Which decompose the matrix into three components such as U, S and V. U and V are the unitary matrices and S is the diagonal matric [17,18]. The SVD is applied into both key frames and watermark.…”

Section: Svd (Singular Value Decomposition)mentioning

confidence: 99%

Fuzzy Rule Based Video Watermarking in DWT-SVD Domain

S¹,

Ramakrishnan²

2021

Preprint

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This paper addresses the issues in video copyright using DWT and SVD. The prevailing algorithms countermeasure various attacks and they do not contemplate on the redundancy of frames in the video. Proposed methodology focuses on the identification of non-redundant frames by introducing a fuzzy model for reducing the processing time. The frequently changed scenes are identified by scene change detection algorithm. The key frames are effectively identified from each scene by fuzzy rules using entropy, absolute mean difference and absolute difference of frame variance of the video frames. DWT is applied to the key frames. The watermark image is divided into number of blocks based on the number of key frames selected in the scene. The order of embedding the watermark block in each scene is different. The SVD is applied to the key frames and watermark. In the embedding process, the singular values of key frame are added to the Principal Component (PC) of the watermark bock. The experimental results show that the proposed methodology is resilient to image processing, frame based attacks and also resolves the false positive problem as well as improves the robustness and imperceptibility of video and watermark.

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“…The watermark image [23] can be directly extracted from the watermarked video frames from the LSBs. The process of watermark extraction is as follows:…”

Section: E Watermark Extraction Processmentioning

confidence: 99%

Video Watermarking for Copyright Protection with Genetic-Based Frame Selection

Alotaibi¹

2019

JKAU Comp IT Sci

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Recently, video watermarking has received much consideration. Several applications in a variety of domains have been implemented, and many are progressing. This paper intends to formulate a novel video watermarking framework that includes three stages: (i) Optimal video frame prediction, (ii) A watermark embedding process, and (iii) A watermark extraction process. In the proposed model, the optimal frame prediction is carried out using the deep belief network (DBN) framework. Initially, randomly chosen frames from each video are used as the input to a genetic algorithm (GA) model that optimally chooses the frames such that the peak signal-tonoise ratio (PSNR) should be maximal. The frames are assigned with a label of one or zero, where a label of one denotes a frame with better PSNR (can select for embedding process) and a label of zero denotes the frame with reduced PSNR (cannot be used for embedding). Consequently, a data library is formed from the obtained results, where each video frame is determined with their graylevel cooccurrence matrix (GLCM) features and labels (can embed or not), which is then trained in the DBN framework, from which the optimal frames can be predicted efficiently while testing. Furthermore, the watermark embedding process and watermark extraction process are carried out, and thus, the image can be embedded within the optimally selected frames.

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A Blind DWT-SCHUR Based Digital Video Watermarking Technique

Cited by 27 publications

References 12 publications

Security of Surveillance Wireless Camera Sensor Network Systems using Embedding Techniques for Authentication

Security of Surveillance Wireless Camera Sensor Network Systems using Embedding Techniques for Authentication

Fuzzy Rule Based Video Watermarking in DWT-SVD Domain

Video Watermarking for Copyright Protection with Genetic-Based Frame Selection

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