Improved security in the genetic algorithm-based image steganography scheme using Hilbert space-filling curve

Yadav, Gyan Singh; Ojha, Aparajita

doi:10.1080/13682199.2019.1570678

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…The spatial linear interpolation planning algorithm is a process of solving the position and attitude of each trajectory interpolation point when the position and attitude of the starting point and end point are known. Because in most cases, when the robot moves along a straight line, its end orientation attitude does not change; so, there is no need to interpolate the end attitude [23]. The position and pose of the two points P 1 ðx 1 , y 1 , z 1 Þ and P 2 ðx 2 , y 2 , z 2 Þ at the beginning and end of the spatial line relative to the global coordinates are known.…”

Section: Rectangular Coordinate Space Straight Line Trajectorymentioning

confidence: 99%

Improved Genetic Algorithm for Intelligent Grinding Trajectory of Industrial Robot Sensor

2022

Journal of Sensors

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In order to study the improved genetic algorithm for intelligent grinding trajectory of industrial robot, a trajectory planning method with optimal energy consumption is proposed. Firstly, the trajectory of the robot is regarded as a series of type value points in space, and each adjacent type value point is connected by a quintic B -spline curve to obtain the trajectory function of the robot. Then, the kinetic energy is taken as the target energy consumption function, and the kinematic and dynamic constraints of each joint are considered at the same time. Finally, the genetic algorithm is improved to optimize the objective energy consumption function. The improved genetic algorithm improves the operation efficiency, local search ability, and real-time performance of the algorithm. Front and rear times during handling were 15.034 s and 17.456 s for 2.422 s. The optimal secondary trajectory planning algorithm is called in the single workstation of the welding robot and the robot welding the bucket with spatial straight line and spatial curve, respectively. Through the time difference, the time used in the spatial linear welding is 5.462 s, and the spatial curve welding time is 12.981 s. The proposed algorithm can be applied to the production of various industrial sensor robots such as welding robot, cutting robot, and spraying robot and improves the working efficiency of robot operation. In addition, the genetic method of multichromosome structure also has a certain reference for solving the general GSTP problem.

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Section: Rectangular Coordinate Space Straight Line Trajectorymentioning

confidence: 99%

Improved Genetic Algorithm for Intelligent Grinding Trajectory of Industrial Robot Sensor

2022

Journal of Sensors

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“…In this paper, Hilbert similarity is proposed to find the better similarity as a way to assure random selection to hide the secret bits at. Therefore, and in order to solve this problem, the maximum similarity is measured between the cover image corresponding block of pixels with a selected block in the randomly generated image key [24]. Technically, block size is proposed to be eight pixels each.…”

Section: A Hilbert Similarity Measurementsmentioning

confidence: 99%

Hilbert Convex Similarity for Highly Secure Random Distribution of Patient Privacy Steganography

Alzubaidy,

Al-Shammary,

Abed

et al. 2023

IEEE Access

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Based on Hilbert Random Secure Distribution, a novel data-hiding method for embedding secret information about the patient in a cover image MRI sample has been proposed. Least significant bit (LSB) and most significant bit (MSB) techniques are applied for the physical hiding. Medical images confidentiality suffers from potential attacks and tracing by an unauthorized access. Technically, distributing the secret text in a random way on the cover image is the core security function of the proposed model. In order to evaluate the performance of the proposed solution, three quality metrics: Peak signal to noise ratio (PSNR), Mean Square Error (MSE) , percentage residual difference (PRD) and Structural Similarity Index measure (SSIM) were computed and compared on ten MRI images. Experimental results showed significant results in comparison with other models and reached average PSNR up to 61 db. Furthermore, the security analysis in case of 512 × 512 image samples show complex probability of distribution based on the Hilbert space model.

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“…e difference calculation can calculate the pixel value of each frame, and the pixel filling is performed through the difference calculation to ensure the effect of the artistic visual image [11]. e filling calculation formula is…”

Section: Art Visual Image Preprocessingmentioning

confidence: 99%

Art Visual Image Transmission Method Based on Cartesian Genetic Programming

Zhao

2021

Scientific Programming

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Because most of the traditional artistic visual image communication methods use the form of modeling and calculation, there are some problems such as long image processing time, low success rate of image visual communication, and poor visual effect. An artistic visual image communication method based on Cartesian genetic programming is proposed. The visual expression sensitivity difference method is introduced to process the image data, the neural network is used to identify the characteristics of the artistic visual image, the midpoint displacement method is used to remove the folds of the artistic visual image, and the processed image is formed under the above three links. The Cartesian genetic programming algorithm is used to encode the preprocessed image, improve the fitness function, select the algorithm to improve the operation, design the image rendering platform, input the processed image to the platform, and complete the artistic visual image transmission. The analysis of the experimental results shows that the image processing time of this method is short, the success rate of visual communication is high, and the image visual effect is good, which can obtain the image processing results satisfactory to users.

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Improved security in the genetic algorithm-based image steganography scheme using Hilbert space-filling curve

Cited by 5 publications

References 19 publications

Improved Genetic Algorithm for Intelligent Grinding Trajectory of Industrial Robot Sensor

Improved Genetic Algorithm for Intelligent Grinding Trajectory of Industrial Robot Sensor

Hilbert Convex Similarity for Highly Secure Random Distribution of Patient Privacy Steganography

Art Visual Image Transmission Method Based on Cartesian Genetic Programming

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