A predictive model-based image watermarking scheme using Regression Tree and Firefly algorithm

Kazemivash, Behnam; Moghaddam, Mohsen Ebrahimi

doi:10.1007/s00500-017-2617-4

Cited by 33 publications

(34 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In order to compare the proposed scheme with the schemes in the literature, some schemes are selected for comparison, which are Mehta et al [18], Kazemivash et al [10], Kazemivash et al [9], and Tsai and Liu [27]. As depicted in Fig.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…Kazemivash et al [10] proposed a scheme based on Lifting Wavelet Transform (LWT) as a strong transform domain for embedding the watermark. Multi-scaling factor is optimized using Firefly algorithm to reach high imperceptibility and robustness.…”

Section: Related Workmentioning

confidence: 99%

“…This literature covers some of the recent research articles that used different MLTs for copyright protection using watermark. However, the articles Mehta et al [18], Kazemivash et al [10], Kazemivash et al [9], and Tsai and Liu [27] are the closest to the proposed scheme where either optimization techniques are used for scaling factor selection, or MLTs are conducted, and in most of them, the same host images with the same sizes are used.…”

Section: Related Workmentioning

confidence: 99%

“…Lines (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25) illustrate the watermark embedding process. In lines (7)(8)(9)(10)(11)(12), the host image and the watermark image are loaded, then the host image is divided into non overlapping blocks of size 8*8 and a number of Sb blocks are selected randomly for the embedding process with keeping their positions in K as a secret key to be used in the extraction process. The watermark image is divided into four parts [wp 1 , wp 2 , wp 3 , wp 4 ], in which each part will be embedded in its corresponding wavelet sub-band.…”

Section: Optimization Processmentioning

confidence: 99%

See 3 more Smart Citations

Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

Houby

Yassin

2020

Multimed Tools Appl

View full text Add to dashboard Cite

Recently the active use of Internet and multimedia technologies has increased the violation of copyright. Digital watermarking has a crucial role in the field of multimedia copyright protection. In this paper, an optimized image watermarking technique based on Discrete Wavelet Transform (DWT) and Hadamard transform is proposed. Genetic Algorithm (GA) is an optimizing technique used to satisfy the tradeoff between robustness and imperceptibility. Blind property is conducted using the estimation capability of Decision Tree (DT). First the host image is transformed using second level DWT, then Hadamard transform is applied on selected DWT sub-bands. Adaptive multiple strength values are computed using GA. The watermark is successfully extracted using the trained DT which estimates the original coefficients needed for the extraction process without the need for the original host image. The proposed technique is evaluated against several types of attacks: compression, median filtering, salt and pepper noise, histogram equalization, blurring, scaling, painting, and cropping. Experimental results show that the proposed watermarking technique is robust against these attacks while keeping good imperceptibility. The proposed technique outperforms the compared techniques according to robustness, imperceptibility, and capacity.

show abstract

Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Optimization Processmentioning

confidence: 99%

See 2 more Smart Citations

Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

Houby

Yassin

2020

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…Non-Blind watermarking was introduced by Navas in which they used different sub band of DWT for hiding the watermark with SVD as hiding method [6]. A novel method based on LWT and firefly Algorithm was presented by blending the optimization technique to estimate the scale factor for more robustness [15]. Based on the review of above related work we came to know that major factors of watermarking are Robustness, Imperceptibility and Capacity.…”

Section: Related Workmentioning

confidence: 99%

DWT-DCT Based copyright Protection In Ycbcr Color Space

Chaturvedi¹,

Sharma²,

Dwivedi³

et al. 2019

IJITEE

View full text Add to dashboard Cite

Digital image watermarking is powerful technique which provide ownership protection and copyright protection. In this paper, a novel watermarking technique based on Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) is presented. YCbCr color model is used for watermark embedding and extraction because of its close resemblance to human visual system. Single level DWT is applied to Luma Component of YCbCr color cover image and then DCT coefficients are taken for watermark embedding process. DCT is applied block by block of size . Binary watermark is scrambled using Arnold transform with k iterations to achieve robustness. Proposed method has been evaluated by many performance evaluation measures such as Peak Signal to Noise Ratio (PSNR), Normalized Correlation (NC) and Computational time. Various watermark attacks are also applied against proposed method, result shows that superiority over other methods.

show abstract

Feature Optimization of Digital Image Watermarking Using Machine Learning Algorithms

Rai

Goyal

Pawar

2021

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

A predictive model-based image watermarking scheme using Regression Tree and Firefly algorithm

Cited by 33 publications

References 39 publications

Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

Wavelet-Hadamard based blind image watermarking using genetic algorithm and decision tree

DWT-DCT Based copyright Protection In Ycbcr Color Space

Feature Optimization of Digital Image Watermarking Using Machine Learning Algorithms

Contact Info

Product

Resources

About