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

Bassel, Atheer; Nordin, Jan; Abdulkareem, Mohammed Basil

doi:10.14257/ijsia.2018.12.2.01

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…As information communication technologies, miniaturized displays, and inexpensive storage devices make progress, the volume of available social multimedia data is increasing exponentially [27][28][29][30][31][32][33]. However, such video data usually include valuable information, but also include information not preferred being exposed to other people such as the face or human body part of other people.…”

Section: Related Workmentioning

confidence: 99%

Extraction of mosaic regions through projection and filtering of features from image big data

Jang

2021

COMSIS J

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When uploading multimedia data such as photos or videos on social network services, websites, and so on, certain parts of the human body or personal information are often exposed. Therefore, it is frequent that the face of a person is blurred out to protect the portrait right of a particular person, and that repulsive objects are covered with mosaic blocks to prevent others from feeling disgusted. In this paper, an algorithm that detects mosaic regions blurring out certain blocks based on the edge projection is proposed. The proposed algorithm initially detects the edge and uses the horizontal and vertical line edge projections to detect the mosaic candidate blocks. Subsequently, geometrical features such as size, aspect ratio and compactness are used to filter the candidate mosaic blocks, and the actual mosaic blocks are finally detected. The experiment results showed that the proposed algorithm detected mosaic blocks more accurately than other methods.

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Section: Related Workmentioning

confidence: 99%

Extraction of mosaic regions through projection and filtering of features from image big data

Jang

2021

COMSIS J

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“…Moreover, if we want a watermarking scheme to be more robust, then watermarked image quality may be sacrificed. In recent years, many bioinspired algorithms are used to solve the aforementioned problems of watermarking, such as firefly algorithm (FA) [54], differential evolution (DE) [26], [55], artificial bee colony (ABC) [6], [32], [51], fruit fly optimization algorithm (FOA) [48], teaching-learning-based optimization (TLB) [47], and particle swarm optimization (PSO) [27], [31], [56]- [60]. PSO is an adaptive population dependent optimization approach that focused on fish education or social behavior of birds gathering.…”

Section: Related Workmentioning

confidence: 99%

“…After that, if a bird moves in a specific order, then every bird in the community attempts to pursue it and get the same destination. Some attractive features of PSO are that it does not need to optimize any functional gradient knowledge, it only uses basic mathematical operators and is conceptually very simple [56]. It is used to solve various problems of optimization in different applications like training on neural networks and minimizing functions [57].…”

Section: G Particle Swarm Optimization (Pso)mentioning

confidence: 99%

A Novel Optimized Semi-Blind Scheme for Color Image Watermarking

2020

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Image watermarking is a robust solution for solving key issues like copyright protection and proof of ownership of digital data. Existing schemes of image watermarking mostly used grayscale or binary images as embedded watermarks, while only a few watermarking schemes are developed for color images. In this paper, we propose a novel robust semi-blind image watermarking scheme based on finite ridgelet transform (FRT), discrete wavelet transform (DWT), singular value decomposition (SVD), particle swarm optimization (PSO), and Arnold transform to protect copyright and verify the authenticity of color images. Firstly, the color image is converted from RGB to YCbCr color space, and the luminance component (Y) is taken into account to insert the watermark data. In this study, the principal component (PC) of the watermark image is directly inserted into the corresponding singular value of the cover image by the scaling factor to avoid the false positive problem (FPP). To further improve security, Arnold transform is applied to process the Y channel of the watermark image before inserting it in the cover image. Besides, PSO optimizes the embedding factor matrices. The qualitative evaluation factors like peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) are used to assess the visual quality, while normalized correlation coefficient (NCC) is used to assess the resemblance between the watermarked and the restored watermarked images. The performance of the proposed scheme is evaluated using geometric, non-geometric, and combinational attacks, and its comparison is performed with different image watermarking schemes to prove its robustness.

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

Abstract: Abstract

Cited by 2 publications

References 9 publications

Extraction of mosaic regions through projection and filtering of features from image big data

Extraction of mosaic regions through projection and filtering of features from image big data

A Novel Optimized Semi-Blind Scheme for Color Image Watermarking

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