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

Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

303
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
303
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

59
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
59
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

12.8K
Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
12.8K
Manipulation and Analysis01:21

Manipulation and Analysis

53
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
53
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

88
Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
88
Fischer Projections02:18

Fischer Projections

13.6K
Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines.
13.6K

You might also read

Related Articles

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

Sort by
Same author

SignBridge Bilingual Sign Language Avatar-Construction Principles and Experts Quality Assessment.

Sensors (Basel, Switzerland)·2026
Same author

Creating Digital Watermarks in Bitmap Images Using Lagrange Interpolation and Bezier Curves.

Journal of imaging·2023
Same journal

Human-AI Interaction in Interventional Radiology: A Narrative Review of Current Applications, Challenges, and Future Directions.

Journal of imaging·2026
Same journal

Coronary Artery Anomalies and Anatomical Variants: Cross-Sectional Diagnostic Imaging and Clinical Background.

Journal of imaging·2026
Same journal

YoLeTooth: A Unified Framework for Joint Tooth Segmentation and Periapical Lesion Detection in Panoramic Radiographs.

Journal of imaging·2026
Same journal

Radiomics-Guided Multi-Sequence Learning for Pathological Complete Response Prediction from Breast MRI with Missing Auxiliary Sequences.

Journal of imaging·2026
Same journal

Cutaneous Thermography in Arthropathies: Quantitative Imaging, Machine Learning, and Clinical Translation.

Journal of imaging·2026
Same journal

Two-Stage Dynamic Synergistic Segmentation Method for Myocardial Pathology.

Journal of imaging·2026
See all related articles

Related Experiment Video

Updated: Aug 24, 2025

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro
08:00

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro

Published on: December 3, 2018

8.5K

A Study of the Information Embedding Method into Raster Image Based on Interpolation.

Elmira Daiyrbayeva1,2, Aigerim Yerimbetova1,3, Ivan Nechta4

  • 1Institute of Information and Computational Technologies Committee of Science of the Ministry of Education and Science of the Republic of Kazakhstan, Almaty 050010, Kazakhstan.

Journal of Imaging
|October 26, 2022
PubMed
Summary
This summary is machine-generated.

This study analyzes the improved neighbor mean interpolation (INMI) steganographic method. INMI demonstrates resistance to regular-singular (RS) steganalysis, showing potential for secure data embedding in images.

Keywords:
LSB steganographyRS analyzeimageinterpolationsecret message

More Related Videos

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.5K
Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.5K

Related Experiment Videos

Last Updated: Aug 24, 2025

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro
08:00

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro

Published on: December 3, 2018

8.5K
Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.5K
Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.5K

Area of Science:

  • Computer Science
  • Information Security
  • Digital Forensics

Background:

  • Steganography is the practice of concealing data within other data.
  • The improved neighbor mean interpolation (INMI) is a steganographic method for embedding messages in raster images.
  • Limited steganalysis exists for the INMI method.

Purpose of the Study:

  • To conduct a steganalysis of the INMI steganographic method.
  • To evaluate the embedding capacity and steganalytic resistance of INMI.
  • To compare INMI's performance against other steganographic systems.

Main Methods:

  • Implementation of the INMI message embedding technique in raster files.
  • Steganalysis performed on a dataset of 800 images (225x225 pixels).
  • Calculation of Type I error and information detection rates using the regular-singular (RS) method.

Main Results:

  • Maximum container capacity for INMI was found to be 21%, varying with image content.
  • Only 7.5% (60 out of 800) of images achieved maximum embedding capacity.
  • The INMI steganographic algorithm exhibited resistance to RS steganalysis.

Conclusions:

  • The INMI method is robust against RS steganalysis.
  • INMI's performance is comparable to the permutation method in terms of steganalysis resistance.
  • Further research is needed to fully understand INMI's capacity limitations and security implications.