Results 1 to 10 of about 9,825,333 (241)

New Color Image Zero-Watermarking Using Orthogonal Multi-Channel Fractional-Order Legendre-Fourier Moments [PDF]

open access: yesIEEE Access, 2021
Zero-watermarking methods provide promising solutions and impressive performance for copyright protection of images without changing the original images. In this paper, a novel zero-watermarking method for color images is envisioned.
Khalid M. Hosny   +2 more
doaj   +5 more sources

Invariant Image Representation Using Novel Fractional-Order Polar Harmonic Fourier Moments

open access: yesSensors, 2021
Continuous orthogonal moments, for which continuous functions are used as kernel functions, are invariant to rotation and scaling, and they have been greatly developed over the recent years.
Chunpeng Wang   +5 more
doaj   +5 more sources

Quaternion fractional-order color orthogonal moment-based image representation and recognition [PDF]

open access: yesEURASIP Journal on Image and Video Processing, 2021
Inspired by quaternion algebra and the idea of fractional-order transformation, we propose a new set of quaternion fractional-order generalized Laguerre orthogonal moments (QFr-GLMs) based on fractional-order generalized Laguerre polynomials.
Bing He   +4 more
doaj   +3 more sources

Efficient Analysis of Large-Size Bio-Signals Based on Orthogonal Generalized Laguerre Moments of Fractional Orders and Schwarz–Rutishauser Algorithm

open access: yesFractal and Fractional, 2023
Orthogonal generalized Laguerre moments of fractional orders (FrGLMs) are signal and image descriptors. The utilization of the FrGLMs in the analysis of big-size signals encounters three challenges.
Eman Abdullah Aldakheel   +4 more
doaj   +3 more sources

Optimized bio-signal reconstruction and watermarking via enhanced fractional orthogonal moments [PDF]

open access: yesScientific Reports
Orthogonal Tchebichef moments of fractional order (FrTMs) serve as descriptors for signals and images. Many fields, including signal analysis and watermarking, have relied heavily on such moments.
Gaber Hassan   +2 more
doaj   +3 more sources

Music score copyright protection based on mixed low-order quaternion Franklin moments. [PDF]

open access: yesPLoS ONE
Due to the rapid growth of the digital music industry, music copyrights have become valuable intangible assets for businesses, offering exclusivity and profitability.
Qizheng Huang   +3 more
doaj   +3 more sources

Image representation based on fractional order Legendre and Laguerre orthogonal moments [PDF]

open access: yesInternational Journal of ADVANCED AND APPLIED SCIENCES, 2021
In this paper, we have introduced new sets of fractional order orthogonal basis moments based on Fractional order Legendre orthogonal Functions (FLeFs) and Fractional order Laguerre orthogonal Functions (FLaFs) for image representation. We have generated a novel set of Fractional order Legendre orthogonal Moments (FLeMs) from fractional order Legendre ...
R. M. Farouk, Qamar A. A. Awad
openaire   +2 more sources

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

open access: yesIEEE Access, 2022
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
Achraf Daoui   +6 more
doaj   +2 more sources

Robust Color Images Watermarking Using New Fractional-Order Exponent Moments

open access: yesIEEE Access, 2021
Robust watermarking is a valuable methodology used in protecting the copyright and securing digital images. In this paper, new fractional-order multi-channel orthogonal exponent moments (MFrEMs) and their invariants to geometric transformations are ...
Khalid M. Hosny   +2 more
doaj   +2 more sources

Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN Autoencoder [PDF]

open access: yesIEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022
This paper presents a fractional one-dimensional convolutional neural network (CNN) autoencoder for denoising the Electroencephalogram (EEG) signals which often get contaminated with noise during the recording process, mostly due to muscle artifacts (MA),
Subham Nagar, Ahlad Kumar
doaj   +2 more sources

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