Efficient encryption of image data in video sequences using discrete orthogonal moments

Rivera-López, José S.; Camacho-Bello, César

doi:10.1117/12.2274256

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…Get size Input 3D Imagen L 2 Reshape K reduced from 77004 s to 0.04 s with GPU, which implementation is improving the time recorded by the Matrix Method (0.73 s). In the case of a larger object like the "Dragon," the improvement of the proposal is more noticeable.…”

Section: Resultsmentioning

confidence: 99%

“…Discrete orthogonal moments have the characteristic of representing 2D and 3D images with minimal redundant information used in different applications for processing and analysis, such as image watermark [1][2][3], image compression [4][5][6], invariant characteristics in pattern recognition [7,8], segmentation [9], noise analysis [10], restoration Image [11], face recognition [12], analysis of medical images [13], classification of images and objects [14,15], texture analysis [16], reconstruction of images and objects [17], analysis of scenes and analysis of objects in 3D [18].…”

Section: Introductionmentioning

confidence: 99%

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Fast computation of 3D Tchebichef moments for higher orders

Rivera-López

Camacho-Bello

Vargas-Vargas

et al. 2021

J Real-Time Image Proc

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This article proposes a new method for the fast and efficient calculation of 3D Tchebichef moments,which are an essential tool for the characterization and analysis of 3D objects. This method integrates the Kronecker tensor product to the computation of 3D Tchebichef moments for higher orders with the advantage of being parallelizable. The experimental results clearly show the benefits and efficacy of the proposed method compared to existing methods. Keywords 3D discrete orthogonal Tchebichef moments • Fast computation • 3D image reconstruction • High-order moments • Kronecker tensor product

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fast computation of 3D Tchebichef moments for higher orders

Rivera-López

Camacho-Bello

Vargas-Vargas

et al. 2021

J Real-Time Image Proc

View full text Add to dashboard Cite

show abstract

“…Moreover, recent developments in algorithms for computing Krawtchouk polynomial coefficients have been proposed to address instability issues associated with the computation of high-order polynomials [19,22,23]. One such approach involves the use of the three-term recurrence relation, which expresses each coefficient of the Krawtchouk polynomial in terms of the previous two coefficients.…”

Section: Introductionmentioning

confidence: 99%

High-Performance Krawtchouk Polynomials of High Order Based on Multithreading

Flayyih,

Al-sudani,

Mahmmod

et al. 2024

Computation

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Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parallel processing capabilities of modern central processing units (CPUs), namely the availability of multiple cores and multithreading. The proposed multi-threaded implementations for computing DKraP coefficients divide the computations into multiple independent tasks, which are executed concurrently by different threads distributed among the independent cores. This multi-threaded approach has been evaluated across a range of DKraP sizes and various values of polynomial parameters. The results show that the proposed method achieves a significant reduction in computation time. In addition, the proposed method has the added benefit of applying to larger polynomial sizes and a wider range of Krawtchouk polynomial parameters. Furthermore, an accurate and appropriate selection scheme of the recurrence algorithm is introduced. The proposed approach introduced in this paper makes the DKraP coefficient computation an attractive solution for a variety of applications.

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Efficient encryption of image data in video sequences using discrete orthogonal moments

Cited by 2 publications

References 16 publications

Fast computation of 3D Tchebichef moments for higher orders

Fast computation of 3D Tchebichef moments for higher orders

High-Performance Krawtchouk Polynomials of High Order Based on Multithreading

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