Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Transformations of Functions III01:20

Transformations of Functions III

278
Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...
278
Open and closed-loop control systems01:17

Open and closed-loop control systems

2.0K
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
2.0K
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

1.2K
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
1.2K
Convolution Properties II01:17

Convolution Properties II

657
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
657
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.1K
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
1.1K
Transformation01:26

Transformation

1.3K
Microbial communities are dynamic environments where cell lysis releases free DNA into the surroundings. Other cells can take up this extracellular DNA through a process known as transformation.When a cell incorporates this foreign DNA into its genome, resulting in genetic modification, the process is known as transformation. Cells capable of this process are termed competent. Competence can be natural, as observed in certain bacteria and archaea, or artificially induced in the...
1.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Image Encryption Algorithm Based on a New Two-Dimensional Chaotic System and Rotating Dial Model.

Entropy (Basel, Switzerland)·2026
Same author

Image Encryption Algorithm Based on a Novel Hyperchaotic Map and 3D Histogram Model.

Entropy (Basel, Switzerland)·2026
Same author

Image Encryption Algorithm Based on Dynamic Rhombus Transformation and Digital Tube Model.

Entropy (Basel, Switzerland)·2025
Same author

Morphology Control of Zr-Based Luminescent Metal-Organic Frameworks for Aflatoxin B1 Detection.

Biosensors·2024
Same author

Achieving a solar-to-chemical efficiency of 3.6% in ambient conditions by inhibiting interlayer charges transport.

Nature communications·2024
Same author

Identifying Factors Affecting the Survival of Patients with HIV-Associated B-Cell Lymphoma Using a Random Survival Forest Model.

Clinical Medicine Insights. Oncology·2024
Same journal

Mental health of healthcare workers in England during the first three years of the COVID-19 pandemic: The NHS CHECK study cohort.

PloS one·2026
Same journal

Research on trajectory tracking control of tracked vehicles based on hydraulic motor system identification and Laguerre-MPC.

PloS one·2026
Same journal

A collaborative cervical precancer screening strategy with concurrent HPV genotyping and visual inspection using alumni of a training centre across Ghana: The Rotary 'Protect Your Pearl' initiative.

PloS one·2026
Same journal

Removal efficiency of pesticide residues on pesticide-spiked Perilla Leaf and Broccoli surfaces using microplasma-treated water.

PloS one·2026
Same journal

Cross-domain zero-shot semantic segmentation for unstructured environments via EVA-CLIP model, ensemble prompt engineering, and optimized text-image matching.

PloS one·2026
Same journal

Adaptive robust sparse representation for face recognition based on weighted and fusion dictionary.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Apr 2, 2026

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
11:15

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Published on: May 30, 2016

26.5K

Color image encryption algorithm based on ∞-shaped transformation and closed-loop control model.

Feng Zhao1, Xiaoqiang Zhang2, Fang Zhu1

  • 1Department of General Education, Anhui Xinhua University, Hefei, Anhui, China.

Plos One
|March 31, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel color image encryption algorithm using an infinity-shaped transformation and closed-loop control for enhanced security. The method offers a large key space and strong resistance to various attacks.

More Related Videos

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
08:39

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Published on: January 28, 2019

10.5K

Related Experiment Videos

Last Updated: Apr 2, 2026

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
11:15

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Published on: May 30, 2016

26.5K
Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
08:39

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Published on: January 28, 2019

10.5K

Area of Science:

  • Computer Science
  • Information Security
  • Cryptography

Background:

  • Color image security is crucial in the digital age.
  • Traditional scrambling-diffusion methods have limitations.

Purpose of the Study:

  • To propose a novel color image encryption algorithm.
  • To enhance image security using an infinity-shaped transformation and closed-loop control.

Main Methods:

  • Merging three color channels and applying row-wise closed-loop diffusion.
  • Scrambling using an infinity-shaped transformation.
  • Applying column-wise closed-loop diffusion for final encryption.

Main Results:

  • Achieved effective inter-channel pixel confusion and diffusion.
  • Key space size of 2^413.
  • Information entropy approaching 8.
  • High sensitivity (NPCR > 99.6%, UACI > 33.4%).

Conclusions:

  • The proposed algorithm offers excellent overall performance.
  • Demonstrates strong robustness against differential, statistical, and brute-force attacks.
  • Provides effective color image encryption.