Efficient Methods for Signal Processing Using Charlier Moments and Artificial Bee Colony Algorithm

Daoui, Achraf; Karmouni, Hicham; Sayyouri, Mhamed; Qjidaa, Hassan

doi:10.1007/s00034-021-01764-z

Cited by 21 publications

(8 citation statements)

References 59 publications

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“…The decrypted signals with the corresponding PRD (%) values are given in the same Figure 8. The results achieved in this figure display that the four bio-signals are decrypted with reconstruction error tending to zero (MSE< 27 10 − and PRD (%) < 12 10 − ). This evidently specifies the high quality of the reconstructed bio-signals by the suggested method.…”

Section: A Reconstruction Errors Analysis Of Biomedical Signalsmentioning

confidence: 87%

“…Discrete orthogonal moments (DOMs) are regarded as powerful descriptors in the field of digital signal and image processing. DOMs are computed based on discrete orthogonal polynomials (DOPs), like Tchebichef [24], Krawtchouk [2], Hahn [25], Meixner [26], Charlier [27], dual Hahn [28], [29] and Racah polynomials [30]. Lately, some discrete orthogonal polynomials involving fractional order have been introduced in the literature.…”

Section: Related Workmentioning

confidence: 99%

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Biomedical Multimedia Encryption by Fractional-Order Meixner Polynomials Map and Quaternion Fractional-Order Meixner Moments

et al. 2022

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Chaotic systems are widely used in signal and image encryption schemes. Therefore, the design of new chaotic systems is always useful for improving the performance of encryption schemes in terms of security. In this work, we first demonstrate the chaotic behavior of fractional order Meixner polynomials (FrMPs) for introducing a new two-dimensional (2D) chaotic system called FrMPs map. This system is very sensitive to any variation by 15 10 − of its control parameters ( and µ β ).Next, we use FrMPs to introduce a new type of orthogonal transforms called quaternion fractional order Meixner moments (QFrMMs). The latter generalize the existing fractional order Meixner moments. To demonstrate the relevance of the proposed FrMPs map and QFrMMs in the field of signal and image processing, they are applied in the development of a new encryption scheme. The main advantage of this scheme is its applicability to the encryption of different types of biomedical data such as multi-biomedical signals, multiple grayscale medical images, color medical image, and grayscale medical image. Several simulation analysis (visual, histogram, runtime, correlation, robustness, etc.) are conducted to verify the efficiency of the proposed scheme. Simulation and comparison results confirm that our encryption method is effective in terms of high security level, high quality of the decrypted information, strong resistance to different types of attacks, etc. These findings support the suitability of the proposed scheme for the secure exchange of biomedical multimedia via a public communication channel.

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Section: A Reconstruction Errors Analysis Of Biomedical Signalsmentioning

confidence: 87%

Section: Related Workmentioning

confidence: 99%

Biomedical Multimedia Encryption by Fractional-Order Meixner Polynomials Map and Quaternion Fractional-Order Meixner Moments

et al. 2022

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“…The decomposition of the input image into a set of blocks is generally carried out to reduce the complexity of the algorithms and to carry out the image transformation. However, the subdivision of the input image into blocks leads to visual blocking artifacts in the reconstruction of these blocs in the transform domain [28]. Furthermore, if only one pixel in the block is tempered by unauthorized persons, the other block pixels are considered as tampered one, resulting in a significant false positive detection problem [3].…”

Section: Related Workmentioning

confidence: 99%

AuCFSR: Authentication and Color Face Self-Recovery Using Novel 2D Hyperchaotic System and Deep Learning Models

Daoui,

Yamni,

Altameem

et al. 2023

Sensors

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Color face images are often transmitted over public channels, where they are vulnerable to tampering attacks. To address this problem, the present paper introduces a novel scheme called Authentication and Color Face Self-Recovery (AuCFSR) for ensuring the authenticity of color face images and recovering the tampered areas in these images. AuCFSR uses a new two-dimensional hyperchaotic system called two-dimensional modular sine-cosine map (2D MSCM) to embed authentication and recovery data into the least significant bits of color image pixels. This produces high-quality output images with high security level. When tampered color face image is detected, AuCFSR executes two deep learning models: the CodeFormer model to enhance the visual quality of the recovered color face image and the DeOldify model to improve the colorization of this image. Experimental results demonstrate that AuCFSR outperforms recent similar schemes in tamper detection accuracy, security level, and visual quality of the recovered images.

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“…In recent years, one-dimensional and two-dimensional discrete orthogonal moments have been gaining importance because of their ability to represent signals and images well in various fields. The applications of discrete orthogonal moments include signal and image reconstruction [17,19,31], face recognition [46], image classification [2,12], image watermarking [57], image encryption [56], images compression [24,33,55], signals compression [3,21,32]. Charlier moment (CMs) represents one type of discrete orthogonal moment [18,38].…”

Section: Introductionmentioning

confidence: 99%

An efficient compression technique for Foetal phonocardiogram signals in remote healthcare monitoring systems

Fathi

Ahmed

Makhlouf

2022

Multimed Tools Appl

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Remote Healthcare Monitoring Systems (RHMs) that employ fetal phonocardiography (fPCG) signals are highly efficient technologies for monitoring continuous and long-term fetal heart rate. Wearable devices used in RHMs still face a challenge that decreases their efficacy in terms of energy consumption because these devices have limited storage and are powered by batteries. This paper proposes an effective fPCG compression algorithm to reduce RHM energy consumption. In the proposed algorithm, the Discrete Orthogonal Charlier Moment (DOCMs) is used to extract features of the signal. The householder orthonormalization method (HOM) is used with the Charlier Moment to overcome the propagation of numerical errors that occur when computing high-order Charlier polynomials. The proposed algorithm’s performance is evaluated in terms of CR, PRD, SNR, PSNR, and QS and provides the average values 18.33, 0.21, 48.85, 68.86, and 90.88, respectively. The results of the comparison demonstrate the proposed compression algorithm’s superiority over other algorithms. It also tested in terms of compression speed and computational efficiency. The results indicate that the proposed algorithm has a high Compression speed (218.672 bps) and high computational efficiency (21.33). Additionally, the results reveal that the proposed algorithm decreases the energy consumption of a wearable device due to the transmission time decreasing for data by 3.68 s.

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Efficient Methods for Signal Processing Using Charlier Moments and Artificial Bee Colony Algorithm

Cited by 21 publications

References 59 publications

Biomedical Multimedia Encryption by Fractional-Order Meixner Polynomials Map and Quaternion Fractional-Order Meixner Moments

Biomedical Multimedia Encryption by Fractional-Order Meixner Polynomials Map and Quaternion Fractional-Order Meixner Moments

AuCFSR: Authentication and Color Face Self-Recovery Using Novel 2D Hyperchaotic System and Deep Learning Models

An efficient compression technique for Foetal phonocardiogram signals in remote healthcare monitoring systems

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