Multiple scaling factors based Semi-Blind watermarking of grayscale images using OS-ELM neural network

Rajpal, Ankit; Mishra, Anurag; Bala, Rajni

doi:10.1109/icspcc.2016.7753622

Cited by 12 publications

(2 citation statements)

References 11 publications

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“…Swarm intelligence inspired by the biological flying kits and nature inspired function in artificial intelligence. The nature of swarm intelligence is meta-heuristic and diverse solution of define problem [33][34][35][36]. In this section describe the two swarm-based algorithms such as PSO and ACO algorithm.…”

Section: Swarm Intelligence Algorithmsmentioning

confidence: 99%

Optimized Features of SIFT Transform Function for Digital Image Watermarking using Hybrid Swarm Intelligence and Neural Network

Kumar¹,

Sharma²

2019

IJRTE

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Authentication of digital multi-media is a challenging task in the current scenario of internet technology for the authentication of digital multi-media data used digital watermarking techniques. The feature-based watermarking techniques provide the robustness of digital watermarking methods. In this paper proposed optimized features based digital watermarking techniques using a neural network. For the process of features, optimization used hybrid swarm intelligence algorithms. The hybrid algorithms are a combination of PSO and ACO. The PSO used as feature optimizer and ACO used for the selection of features point for the processing of neural network models. Two neural networks models used BP and RBF. The property of both models is different for the processing of data and desired output for the enhancement of the proposed model used cascaded neural network models using BP and RBF. The cascaded models generate dynamic patterns for the embedding of a digital watermark. The dynamic patterns provide the randomness of the pixel value and decrease the value of attack predication. The proposed algorithms have been tested on an extensive database of 300 images. The analysis of the proposed algorithm is satisfactory against different types of attacks and enhance the strength of robustness.

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Section: Swarm Intelligence Algorithmsmentioning

confidence: 99%

Optimized Features of SIFT Transform Function for Digital Image Watermarking using Hybrid Swarm Intelligence and Neural Network

Kumar¹,

Sharma²

2019

IJRTE

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“…Using the Bat optimization algorithm, Pourhadi and Mahdavi [41] presented a robust and optimized digital image watermarking scheme based on the stationary wavelet transform to correct the geometric attack. Rajpal et al [42] proposed a watermarking scheme to optimize multiple scaling factors using online sequential extreme learning machine. Sharma and Mir [43] used the meta-heuristic optimization approach to develop an optimized watermarking scheme.…”

Section: Introductionmentioning

confidence: 99%

Robust Medical Image Watermarking Scheme Using PSO, LWT, and Hessenberg Decomposition

et al. 2023

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Digital imaging is a technology that is extensively employed in diverse diagnostic examinations such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound imaging, among other modalities. Transferring a patient’s diagnostic images and medical data to a specialist physician in a distinct geographical location is conducted to facilitate an accurate diagnosis. The safeguarding of patient data privacy and confidentiality is ensured through the utilisation of smart hospital applications for medical data security. The current research presents the effective utilisation of lifting wavelet transform (LWT) and Hessenberg-based particle swarm optimization in order to generate resilient and safeguarded watermarks on ultrasound images. The empirical evidence suggests that our innovative approach outperforms our prior methodology, established through extensive testing. The watermark’s imperceptibility and accuracy are exemplified by its capacity to sustain a superior structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR), even amidst diverse image processing assaults.

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Fast Semi-blind Color Image Watermarking Scheme Using DWT and Extreme Learning Machine

Mishra

Rajpal

Bala

2017

Computational Science and Its Applications – ICCSA 2017

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Multiple scaling factors based Semi-Blind watermarking of grayscale images using OS-ELM neural network

Cited by 12 publications

References 11 publications

Optimized Features of SIFT Transform Function for Digital Image Watermarking using Hybrid Swarm Intelligence and Neural Network

Optimized Features of SIFT Transform Function for Digital Image Watermarking using Hybrid Swarm Intelligence and Neural Network

Robust Medical Image Watermarking Scheme Using PSO, LWT, and Hessenberg Decomposition

Fast Semi-blind Color Image Watermarking Scheme Using DWT and Extreme Learning Machine

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