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

Curvature and Its Interpretation01:25

Curvature and Its Interpretation

Curvature describes how rapidly a curve changes direction at a particular point. A curve with a small curvature bends gently, while a curve with a large curvature turns sharply. For a space curve, the position of a moving object can be described by a vector-valued function r(t), where t often represents time. The direction of motion is determined by the tangent vector, and the unit tangent vector is obtained by normalizing the derivative of the position vector.The unit tangent vector gives the...
Degree of Curvature and Radius of Curvature01:19

Degree of Curvature and Radius of Curvature

The degree of curvature and the radius of curvature are fundamental concepts in determining the sharpness or smoothness of a curve. The degree of curvature is a measure of how steeply a curve bends and can be determined using the chord basis or the arc basis. In the chord basis method, the degree of curvature is defined as the central angle subtended by a chord of 30.48 meters, helping in the calculation of the radius of the curve. The arc basis method defines the degree of curvature as the...
Deformations in a Symmetric Member in Bending01:18

Deformations in a Symmetric Member in Bending

When analyzing the deformation of a symmetric prismatic member subjected to bending by equal and opposite couples, it becomes clear that as the member bends, the originally straight lines on its wider faces curve into circular arcs, with a constant radius centered at a point known as Point C. This phenomenon helps to understand the stress and strain distribution within the member more clearly.
When the member is segmented into tiny cubic elements, it is observed that the primary stress...
Bending of Curved Members - Strain Analysis01:14

Bending of Curved Members - Strain Analysis

The mechanics of deformation in curved members, such as beams or arches, under bending moments, involve complex responses. When such a member, symmetric about the y-axis and shaped like a segment of a circle centered at point C, is subjected to equal and opposite forces, its curvature and surface lengths change significantly. This alteration results in the shift of the curvature's center from C to C', indicating a tighter curve.
The important part of bending analysis for such a member is the...
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...
Unsymmetric Bending01:18

Unsymmetric Bending

Unsymmetrical bending occurs when the bending moment applied to a structural member does not align with its principal axis. This misalignment leads to complex stress distributions and deflection patterns that differ from those in symmetrical bending, and are essential for designing structures to withstand different loading conditions. In unsymmetrical bending, the neutral axis—where stress is zero—does not necessarily align with the geometric axes of the cross-section. The orientation of the...

You might also read

Related Articles

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

Sort by
Same author

Socio-economic burden and health-related quality of life in patients with rare diseases during the COVID-19 pandemic: abridged secondary publication.

Hong Kong medical journal = Xianggang yi xue za zhi·2026
Same author

Client Service Receipt Inventory for rare genetic diseases in Hong Kong: abridged secondary publication.

Hong Kong medical journal = Xianggang yi xue za zhi·2024
Same author

Asthma admission among children in Hong Kong during the first year of the COVID-19 pandemic.

Pediatric pulmonology·2022
Same author

Mental health & maltreatment risk of children with special educational needs during COVID-19.

Child abuse & neglect·2022
Same author

Infected pancreatic pseudocyst following severe dengue infection.

The Medical journal of Malaysia·2021
Same author

Role of healthcare professionals in cancer screening.

Hong Kong medical journal = Xianggang yi xue za zhi·2020
Same journal

Mask-guided Asymmetric Contrastive and Semantic Alignment for Unsupervised Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Learning Gaze Synthesizer via 3D-eye Controlled Diffusion and Cross-domain Feature Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Underlying Semantic Diffusion for Effective and Efficient In-Context Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation without Information Leakage.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Location Matters: Frequency-Spatial Dual Space Adaptation for Cross-Domain Few-Shot Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

Related Experiment Video

Updated: Jul 7, 2026

Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools
07:58

Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools

Published on: November 11, 2020

Multiscale curvature-based shape representation using B-spline wavelets.

Y P Wang1, S L Lee, K Toraichi

  • 1Sch. of Med., Washington Univ., St. Louis, MO 63110, USA. wyp@cauchy.wustl.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 13, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a novel multiscale curvature-based shape representation for efficient curve data compression. Utilizing B-spline wavelets, it enhances curve analysis and interpolation for improved data handling.

More Related Videos

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
11:00

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Related Experiment Videos

Last Updated: Jul 7, 2026

Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools
07:58

Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools

Published on: November 11, 2020

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
11:00

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Area of Science:

  • Computer Vision
  • Geometric Modeling
  • Signal Processing

Background:

  • Traditional curve representations can be complex and computationally intensive.
  • Gaussian scale-space has limitations in terms of algorithmic efficiency.
  • Efficient curve data compression is crucial for various applications.

Purpose of the Study:

  • To present a new multiscale curvature-based shape representation technique.
  • To apply this technique for effective curve data compression using B-spline wavelets.
  • To introduce a novel coarse-to-fine matching algorithm for dominant point detection.

Main Methods:

  • Implementation of curve evolution in B-spline scale-space.
  • Efficient estimation of multiscale curvature functions using B-spline wavelet transforms.
  • Development of a coarse-to-fine matching algorithm based on curvature scale-space images.

Main Results:

  • Demonstration of a new multiscale curvature-based shape representation.
  • Successful application to curve data compression.
  • Automatic detection of dominant points for curve interpolation.

Conclusions:

  • The proposed B-spline wavelet-based method offers an efficient approach to curve data compression.
  • The technique effectively utilizes multiscale curvature information for shape representation.
  • The developed algorithm facilitates accurate dominant point detection and curve interpolation.