An Invisible Image Watermarking Based On Modified Particle Swarm Optimization (PSO) Algorithm (original) (raw)

An additive image watermarking method based on particle swarm optimization

Many researchers were used the additive method of digital watermarking images which we quote for example Anuradha and Rudresh Pratap Singh (2006) [1]. However, this paper proposes an additive watermarking method by invoking Particle Swarm Optimization (PSO) technique in wavelet domain to improve this scheme of watermarking. To avoid that the watermarking lose its robustness and imperceptibility and extract the watermark under the perfect performance, PSO is fused with the method proposed in [1] which used to insert the watermark in the approximation subband LL3 and which did not apply any type of image processing in order to show its reliability against various types of attacks, except that they show its PSNR after watermarking. In this paper, the main focused on watermarking is that all coefficients are selected from the LH3 subband of watermark to embed it in the same subband of the original image. Result analysis shows that the proposed algorithm certainly outperforms the additive method which doesn’t use PSO and the appropriate decomposition level.

Hybrid particle swarm optimization for robust digital image watermarking

academicjournals.org

This paper presents an image watermarking algorithm for the optimization between robustness and transparency which is recently considered as one of the most challenging issues. The novelty is to associate the Hybrid Particle Swarm Optimization (HPSO), instead of a single optimization, as a model with singular value decomposition (SVD). To embed and extract the watermark, the singular values of the blocked host image are modified according to the watermark and scaling factors. A series of training patterns are constructed by employing between two images. Moreover, the work takes accomplishing maximum robustness and transparency into consideration. HPSO method is used to estimate the multiple parameters involved in the model. Simulation results demonstrated that the proposed scheme can effectively improve the quality of the watermarked image and resist common image manipulations such as adding noise, resizing compression, tempering, etc. and some geometric attacks.

A robust SVD-based image watermarking using a multi-objective particle swarm optimization

Opto-Electronics Review, 2014

The major objective in developing a robust digital watermarking algorithm is to obtain the highest possible robustness with− out losing the visual imperceptibility. To achieve this objective, we proposed in this paper an optimal image watermarking scheme using multi−objective particle swarm optimization (MOPSO) and singular value decomposition (SVD) in wavelet do− main. Having decomposed the original image into ten sub−bands, singular value decomposition is applied to a chosen detail sub−band. Then, the singular values of the chosen sub−band are modified by multiple scaling factors (MSF) to embed the sin− gular values of watermark image. Various combinations of multiple scaling factors are possible, and it is difficult to obtain optimal solutions. Thus, in order to achieve the highest possible robustness and imperceptibility, multi−objective optimiza− tion of the multiple scaling factors is necessary. This work employs particle swarm optimization to obtain optimum multiple scaling factors. Experimental results of the proposed approach show both the significant improvement in term of imperceptibility and robustness under various attacks.

A particle swarm optimization and block-SVD-based watermarking for digital images

TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES

The major issues in most watermarking schemes are security, reliability, and robustness against attacks. To achieve these objectives in a watermarking algorithm, the selection of a scale factor to embed the watermark into the host image is a challenging problem. In this paper, a block singular value decomposition (SVD)-based reliable, robust, secure, and fast watermarking scheme is proposed that uses particle swarm optimization (PSO) in the selection of the scale factor. SVD is applied here on the nonoverlapping blocks of LL wavelet subbands. Selected singular values of these blocks are modified with the pixel values of the watermark image. Selected locations of these singular values increase security. In addition, the scale factor using PSO for embedding the watermark increases the robustness and imperceptibility of the proposed scheme. Direct embedding of the watermark image into the host image and the use of block-SVD makes the scheme faster. Comparative analysis with an existing algorithm shows that the proposed technique performs well during most types of noise attacks and removes the diagonal line problem present in the extracted watermark image.

IJERT-Dwt and Particle Swarm Optimization Based Digital Image Watermarking

International Journal of Engineering Research and Technology (IJERT), 2013

https://www.ijert.org/dwt-and-particle-swarm-optimization-based-digital-image-watermarking https://www.ijert.org/research/dwt-and-particle-swarm-optimization-based-digital-image-watermarking-IJERTV2IS90685.pdf This is the age of digital technology. There are amazing development has been made in the digital technology. now a day there are many work which is necessary for human used in the form of digital such as electronic publishing and advertising, transaction processing, digital image and libraries, web newspapers and magazines, network video and audio etc. These are mainly represented in digital form but due to its digital form its duplication, piracy and modification are easy. Hence to reduce these problems and increase its security various different type of watermarking is used. In this paper we proposed a secure optimized watermarking scheme for digital images, which is based on the particle swarm optimization. For embedding process we use the discrete wavelet transform for the cover image transformation and particle swarm optimization (PSO) which is based on co-relation coefficient are used to detect the high energy coefficient watermark bit in the cover image and then hide the watermark to the cover image. Then different type of attacks is employed to the watermarked image to access it robustness and imperceptibility. The performance of the scheme is evaluated by the PSNR and Correlation coefficient. The proposed scheme provides a good imperceptibility and robust for various attacks.

Dwt and Particle Swarm Optimization Based Digital Image Watermarking

This is the age of digital technology. There are amazing development has been made in the digital technology. now a day there are many work which is necessary for human used in the form of digital such as electronic publishing and advertising, transaction processing, digital image and libraries, web newspapers and magazines, network video and audio etc. These are mainly represented in digital form but due to its digital form its duplication, piracy and modification are easy. Hence to reduce these problems and increase its security various different type of watermarking is used. In this paper we proposed a secure optimized watermarking scheme for digital images, which is based on the particle swarm optimization. For embedding process we use the discrete wavelet transform for the cover image transformation and particle swarm optimization (PSO) which is based on co-relation coefficient are used to detect the high energy coefficient watermark bit in the cover image and then hide the watermark to the cover image. Then different type of attacks is employed to the watermarked image to access it robustness and imperceptibility. The performance of the scheme is evaluated by the PSNR and Correlation coefficient. The proposed scheme provides a good imperceptibility and robust for various attacks.

A New Robust and Imperceptible Image Watermarking Scheme Based on Hybrid Transform and PSO

International Journal of Intelligent Systems and Applications, 2018

In this paper, a new robust and imperceptible digital image watermarking scheme that can overcome the limitation of traditional wavelet-based image watermarking schemes is proposed using hybrid transforms viz. Lifting wavelet transform (LWT), discrete cosine transform (DCT) and singular value decomposition (SVD). The scheme uses canny edge detector to select blocks with higher edge pixels. Two reference sub-images, which are used as the point of reference for watermark embedding and extraction, have been formed from selected blocks based on the number of edges. To achieve a better trade-off between imperceptibility and robustness, multiple scaling factors (MSF) have been employed to modulate different ranges of singular value coefficients during watermark embedding process. Particle swarm optimization (PSO) algorithm has been adopted to obtain optimized MSF. The performance of the proposed scheme has been assessed under different conditions and the experimental results, which are obtained from computer simulation, verifies that the proposed scheme achieves enhanced robustness against various attacks performed. Moreover, the performance of the proposed scheme is compared with the other existing schemes and the results of comparison confirm that our proposed scheme outperforms previous existing schemes in terms of robustness and imperceptibility.

Literature Survey on Watermarking Schemes Using Optimization Techniques

In the world of internet, trillions of bits of information and data are produced in every fraction of second. Thus transferring of the data over the internet needs to be protected from the intruders. Digital watermarking technique has emerged as an innovative technology to protect the data from imposters. This paper focuses different types of transform based approaches and optimization techniques used in digital watermarking. The paper reviews detailed study of particle swarm optimization and proposed methods by taking advantage of combining PSO with different watermarking schemes. The Robustness of the digital watermark implies how effective water marked image against various noise attacks. Thus it has been taken as important parameter for testing the robustness and this can be verified by evaluating NCC (Normalized Cross Correlation value) and PSNR (Peak Signal to Noise Ratio)

DWT-SVD based digital image watermarking using swarm intelligence

2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), 2016

In this paper, a digital image watermarking technique based on Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) is proposed. For embedding the watermark, cover image is decomposed into different subbands using 2-level DWT. SVD is applied on both medium frequency subbands after 2level decomposition of cover image. A watermark image is splitted into two equal images on column basis. These images are again resized to the size of original watermark image by zero padding. The singular value matrices of medium frequency subbands of cover image are modified by splitted watermark images using suitable scale factor obtained by Particle Swarm Optimization (PSO). Again SVD is applied on these modified singular value matrices. Inverse SVD is applied on these singular value matrices along with respective orthogonal matrices of subbands to recover the modified wavelet subbands. The Inverse DWT on these modified subbands along with remaining subbands of cover image makes the watermarked image. Extracted spitted watermark images are added together to reconstruct the original watermark. The Analysis and experimental results show that the proposed technique is more robust against common image manipulation attacks.

An adaptive watermarking approach based on weighted quantum particle swarm optimization

Neural Computing and Applications, 2015

In this paper, we propose a novel optimal singular value decomposition (SVD)-based image watermarking approach that uses a new combination of weighted quantum particle swarm optimization (WQPSO) algorithm and a human visual system (HVS) model for both the hybrid discrete wavelet transform and discrete cosine transform (DCT). The proposed SVD-based watermarking approach initially decomposes the host image into subbands; afterwards, singular values of the DCT of the lower sub-band of the host image are quantized using a set of optimal quantization steps deduced from a combination of the WQPSO algorithm and the HVS model. To evaluate the performance of the proposed approach, we present tests on different images. The experimental results show that the proposed approach yields a watermarked image with good visual definition; at the same time, the embedded watermark was robust against a wide variety of common attacks, including JPEG compression, Gaussian noise, salt and pepper noises, Gaussian filters, median filters, image cropping, and image scaling. Moreover, the results of various experimental analyses demonstrated the superiority of the WQPSO approach over other optimization techniques, including classical PSO and QPSO in terms of local convergence speed, resulting in a better balance between global and local searches of the watermarking algorithm.