A wavelet-based particle swarm optimization algorithm for digital image watermarking

Tao, Hai; Zain, Jasni Mohamad; Ahmed, Mohammad Masroor; Abdalla, Ahmed N.; Wang, Jing

doi:10.3233/ica-2012-0392

Cited by 88 publications

(46 citation statements)

References 32 publications

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“…Earlier, Smith [58] reported that EEG signals are normal during the early stage of AD, but as the disease progresses, alpha waves disappear and slow waves become more apparent. In some cases, periodic sharp Bhat [48,64,65] have advanced the idea that adroit integration of three computing paradigms, time-frequency signal processing [66][67][68] , chaos theory and nonlinear methods [69,70] , and pattern recognition techniques such as artificial neural networks [71][72][73] is the best approach to analyze nonstationary and highly chaotic signals. Significant features can be extracted by nonlinear dynamics and classified using different data-mining techniques and neural networks [74] .…”

Section: Eeg-based Diagnosis Of Admentioning

confidence: 99%

Clinical Neurophysiological and Automated EEG-Based Diagnosis of the Alzheimer's Disease

Bhat¹,

Acharya

Dadmehr³

et al. 2015

Eur Neurol

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Alzheimer's disease (AD) is a progressive disorder affecting intellectual, behavioral and functional abilities. It is associated with age and pathological alterations leading to the formation of amyloid plaques and tangles. It is the most common source of dementia in the older population, which varies in its degrees of severity. We are yet to find efficient methods of diagnosis of AD, as its symptoms vary among individuals. This paper presents a review of recent research on the clinical neurophysiological and automated electroencephalography-based diagnosis of the AD. Various therapeutic measures are also discussed briefly.

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Section: Eeg-based Diagnosis Of Admentioning

confidence: 99%

Clinical Neurophysiological and Automated EEG-Based Diagnosis of the Alzheimer's Disease

Bhat¹,

Acharya

Dadmehr³

et al. 2015

Eur Neurol

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“…PSO [40] is motivated from the social behavior of organism such as bird flocking or fish schooling. It attempts to mimic the natural process of group communication in a wide range of domains and can be used to solve many different problems.…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

“…Recently, particle swarm optimization (PSO) wasevolved into the watermarking system. Hai Tao [40] applied PSO for the optimization of scaling factors to improve the robustness of watermarking scheme. 3-level DWT is used for feature extraction and PSO for optimization.…”

mentioning

confidence: 99%

A Normalized SVD based Image Watermarking with an Enhanced Robustness and Imperceptibility

R¹,

P²

2017

IJET

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Digital Image watermarking is one of the most active and challenging subjects in the information hiding research because it is an efficient solution to protect the copyright of the digital media. This paper proposes a new robust watermarking approach based on the selection of singular features of host image into which the watermark has to embed. The host image initially subjected to a normalization process to find the invariant features and then the obtained invariant features are subjected to Integer Wavelet Transform ( I. INTRODUCTION Digital Image Watermarking [1,2] is the process of insertion of image watermark in media content and its extraction, ifrequired, for authentication or ownership verification ofmedia content. A digital image watermark is a piece of informationthat is hidden directly in media content, in such a way thatit is imperceptible to a human observer [3]. Different types of watermarkingmethods for digital contents have been developed thatare classified into different categories depending upon theuse and the requirement of information required for theextraction/detection of watermark. To check the authenticityof a digital content fragile watermarking is used while, forthe purpose of copyright protection, robust watermarking isutilized. This classification is application-dependent. Basedon the information required for the extraction/detectionprocess watermarking schemes can be classified into blind,semi-blind, and non-blind categories. Also, one more categorizationis possible depending upon the domain of embeddingof watermark: spatial and frequency. A detailed reviewof watermarking schemes can be found in [4,5]. In digital image watermarking, there will be a common problem rises at embedding phase. i.e., the optimization of embedding constant. This constant varies from image to image and also varies based on environments. Hence there is a need to optimize embedding constant such that the watermarked image must be robust and imperceptible to any type of environments. Generally, the artificial intelligence techniques such as Genetic algorithm (GA), Particle swarm optimization (PSO), Ant colony optimization (ACO) etc., techniques will be used for optimization purposes. In [6], a novel watermarking approach was proposed by combining the both GA and PSO to obtain an improved performance in watermarking criterion. However, [6] decomposes the image through the most popular Discrete wavelet transform (DWT) which is having main problem of information loss. Due to the down sampling process in DWT, the extracted watermark and also the host image can't recover entire information. Thus, the quality of the watermark will be reduced. In [7], a block based watermarking is proposed based on Discrete Wavelet Transform (DWT) and Singular Vale decomposition (DWT). Initially, the host image was divided into the blocks of size 8X8 and then processed for DWT. From the obtained sub bands, the approximation band was subjected to SVD. Similarly all blocks are processed and the largest singular value is sele...

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“…SA can identify a good solution quickly but may fluctuate around the local optima due to the lack of the memory mechanism. Additionally, several swarm intelligence algorithms such as ACO [12], particle swarm optimization (PSO) [17,18,45,48,52,53] and HBMO [51], were applied to process planning and scheduling. Compared with the other most known heuristic algorithms such as GA, SA and ACO, HBMO has a better performance in computational effectiveness and stability.…”

Section: Algorithms For Process Planning and Schedulingmentioning

confidence: 99%

A hybrid optimization approach for sustainable process planning and scheduling

Cai

et al. 2015

ICA

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Abstract. Process planning and scheduling are important stages in manufacturing, and good strategies can significantly improve the energy performance of manufacturing to achieve sustainability. In this paper, an innovative optimization approach has been developed to facilitate sustainable process planning and scheduling. In the approach, honey-bee mating and annealing processes are simulated to optimize multi-objectives including energy consumption, makespan and the balanced machine utilization. Experiments on practical cases show that the optimization results from this approach are promising in comparison with those from a genetic algorithm, a honey bee mating optimization algorithm, ant colony optimization and a simulated annealing algorithm, respectively.

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A wavelet-based particle swarm optimization algorithm for digital image watermarking

Cited by 88 publications

References 32 publications

Clinical Neurophysiological and Automated EEG-Based Diagnosis of the Alzheimer's Disease

Clinical Neurophysiological and Automated EEG-Based Diagnosis of the Alzheimer's Disease

A Normalized SVD based Image Watermarking with an Enhanced Robustness and Imperceptibility

A hybrid optimization approach for sustainable process planning and scheduling

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