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Related Concept Videos

Histogram01:05

Histogram

The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
Probability Histograms01:17

Probability Histograms

A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...
Second Uniqueness Theorem01:16

Second Uniqueness Theorem

Consider a region consisting of several individual conductors with a definite charge density in the region between these conductors. The second uniqueness theorem states that if the total charge on each conductor and the charge density in the in-between region are known, then the electric field can be uniquely determined.
In contrast, consider that the electric field is non-unique and apply Gauss's law in divergence form in the region between the conductors and the integral form to the surface...
Legal Guidelines for Documentation01:06

Legal Guidelines for Documentation

The legal guidelines for nursing documentation are essential for ensuring accurate, professional, and ethical recording of patient care. The guidelines are discussed here:

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Related Experiment Videos

Authenticity preservation with histogram-based reversible data hiding and quadtree concepts.

Hsiang-Cheh Huang1, Wai-Chi Fang

  • 1Department of Electrical Engineering, National University of Kaohsiung, 700 University Road, Kaohsiung 811, Taiwan. huang.hc@gmail.com

Sensors (Basel, Switzerland)
|December 14, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel reversible data hiding algorithm for enhanced information security. The new method improves data embedding capacity while maintaining high image quality and comparable side information.

Keywords:
capacityhistogramimperceptibilityquadtreereversible data hidingside information

Related Experiment Videos

Area of Science:

  • Information Security
  • Digital Image Processing
  • Steganography

Background:

  • Authenticity verification in identification systems is crucial.
  • Reversible data hiding is a key technique for secure information embedding and recovery.
  • Evaluating reversible data hiding requires assessing imperceptibility, capacity, and side information.

Purpose of the Study:

  • To develop a novel reversible data hiding algorithm.
  • To improve data embedding capacity compared to conventional methods.
  • To maintain high output image quality and comparable side information.

Main Methods:

  • Developed a new algorithm leveraging characteristics of original images for data embedding.
  • Employed reversible data hiding techniques for encoding and decoding secret information.
  • Evaluated algorithm performance based on capacity, imperceptibility, and side information size.

Main Results:

  • The proposed algorithm demonstrates increased data embedding capacity.
  • Output image quality (imperceptibility) is comparable to existing methods.
  • Side information generated is also comparable to conventional approaches.

Conclusions:

  • The developed algorithm offers improved performance in reversible data hiding.
  • Simulation results confirm the algorithm's applicability and effectiveness.
  • The method provides a viable solution for secure data embedding in identification systems.