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

Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the time...
Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position with respect to time...
Curvilinear Motion: Normal and Tangential Components01:27

Curvilinear Motion: Normal and Tangential Components

When a car traverses a curved road, its motion can be elucidated by breaking it down into tangential and normal components. The car-centric coordinates attached to the vehicle move with it.
The positive direction of the t-axis aligns with the increasing position of the car along the curved path, denoted by the unit vector ut. Simultaneously, the n-axis, perpendicular to the t-axis, dissects the curved path into differential arc segments, each forming the arc of a circle with a radius of...
Distance Corrections01:15

Distance Corrections

To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...
Spherical Coordinates01:23

Spherical Coordinates

Spherical coordinate systems are preferred over Cartesian, polar, or cylindrical coordinates for systems with spherical symmetry. For example, to describe the surface of a sphere, Cartesian coordinates require all three coordinates. On the other hand, the spherical coordinate system requires only one parameter: the sphere's radius. As a result, the complicated mathematical calculations become simple. Spherical coordinates are used in science and engineering applications like electric and...

You might also read

Related Articles

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

Sort by
Same author

High-performance electrochemical sensing of 2-aminophenol enabled by a boron-doped diamond electrode.

RSC advances·2026
Same author

From Single Atom to Five-Atom Cluster Catalysts on Boron-Doped Diamond: Interface Engineering and Dynamic Active Sites Exploration for Acidic OER.

The journal of physical chemistry letters·2026
Same author

Research progress of high-entropy catalysts in electrochemical oxidation of organic small molecules.

Chemical communications (Cambridge, England)·2026
Same author

d-Orbital modulation of high-entropy sulfides with amorphous/crystalline heterostructures for simultaneous hydrogen production and sulfur recovery.

Chemical science·2026
Same author

Electronic Structure Modulation in High-Entropy@Cu<sub><i>x</i></sub>S<sub><i>y</i></sub> Heterostructured Nanorods via Interface Engineering for Enhanced Multifunctional Electrocatalysis.

Inorganic chemistry·2026
Same author

A relative methylation ordering biomarker of lactylation-related genes predicts prognosis and therapeutic response in cutaneous melanoma.

Epigenetics·2026

Related Experiment Video

Updated: May 26, 2026

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration
07:03

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration

Published on: February 23, 2017

Camera lens radial distortion correction using two-view projective invariants.

Xin Du1, Hongdong Li, Yunfang Zhu

  • 1Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China. duxin@zju.edu.cn

Optics Letters
|December 20, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel, noniterative method for automatic radial lens distortion removal in images. The approach enhances accuracy by decoupling distortion estimation from other camera parameters, improving feature point correspondence.

More Related Videos

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
08:04

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Published on: December 4, 2013

Related Experiment Videos

Last Updated: May 26, 2026

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration
07:03

Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration

Published on: February 23, 2017

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
08:04

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Published on: December 4, 2013

Area of Science:

  • Computer Vision
  • Geometric Imaging
  • Photogrammetry

Background:

  • Radial lens distortion is a common artifact in images, affecting geometric accuracy.
  • Existing methods for distortion correction often rely on iterative algorithms that can be slow and prone to local minima.
  • Accurate camera calibration and distortion removal are crucial for many computer vision applications.

Purpose of the Study:

  • To propose a novel, noniterative method for automatic radial lens distortion removal.
  • To leverage projective geometry and algebraic invariants for distortion parameter estimation.
  • To improve the reliability and robustness of distortion correction compared to conventional iterative methods.

Main Methods:

  • Derived algebraic equations relating invariants to radial distortion parameters for planar scenes.
  • Developed a noniterative procedure to solve the system of equations.
  • Implemented a kernel-voting scheme for robust selection of the optimal solution.

Main Results:

  • The noniterative method effectively removes radial lens distortion from image feature point correspondences.
  • The approach demonstrates improved reliability by decoupling distortion estimation.
  • Experiments with synthetic and real image data yielded satisfactory results.

Conclusions:

  • The proposed noniterative method offers a robust and efficient solution for automatic radial lens distortion correction.
  • Decoupling distortion estimation enhances the reliability of results in computer vision tasks.
  • This technique provides a valuable advancement for accurate image analysis and geometric reconstruction.