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Parametric Surfaces01:30

Parametric Surfaces

A parametric surface in three-dimensional space is defined through a vector-valued function\begin{equation*}\mathbf{r}(u, v) = x(u, v)\mathbf{i} + y(u, v)\mathbf{j} + z(u, v)\mathbf{k}\end{equation*}where u and v are parameters within a specified domain D in the uv-plane. The functions x(u, v), y(u, v), and z(u, v) define the coordinates of points on the surface. As u and v vary over D, the position vector r(u, v) traces a continuous surface in space. This parametric representation is essential...
Curves Defined by Parametric Equations01:21

Curves Defined by Parametric Equations

A baseball hit into the air follows a parabolic trajectory when air resistance is neglected. The motion can be described within a two-dimensional coordinate system, where both the horizontal displacement and vertical height are functions of time. Instead of expressing the trajectory as a single function of position, the motion is modeled using parametric equations: one function for the horizontal position and another for the vertical position as time progresses. Let the horizontal position be...
Tangent Planes to a Parametric Surface01:22

Tangent Planes to a Parametric Surface

A tangent plane provides a linear approximation to a curved surface at a specific point, capturing the local behavior of the surface. It can be understood as the plane that just touches the surface at that point and is defined by the tangent directions of curves lying on the surface. These tangent directions arise naturally when the surface is described parametrically, allowing systematic construction of the plane.For a surface expressed in parametric form, the position of any point is...
Bending of Curved Members - Neutral Surface01:16

Bending of Curved Members - Neutral Surface

In curved beams, unlike straight beams, the stress distribution across the cross-section is not uniform due to the beam's curvature. This non-uniformity arises because the neutral axis, where stress is zero, does not align with the centroid of the section. In a curved beam, the strain varies along the section as a function of the distance from the neutral axis.
Consider the curved member described in the previous lesson. According to Hooke's law, which relates stress to strain within the...
Calculus with Parametric Curves: Surface Areas01:30

Calculus with Parametric Curves: Surface Areas

A parametric curve is a description of a path in the plane where both the x and y coordinates are functions of a single parameter, typically denoted t. When such a curve is revolved about an external axis lying in the same plane, it generates a surface of revolution in three dimensions. The surface area of this rotated shape depends fundamentally on two aspects: the geometry of the original curve and how far it lies from the chosen axis of rotation.A torus is a classical surface of revolution...
Level Curves and Contour Maps01:22

Level Curves and Contour Maps

Level curves and contour maps provide a way to visualize functions of two variables on a two-dimensional plane. A useful example is a topographic map, where curved lines represent locations that share the same elevation. In mathematics, these curves are called level curves or contour lines. Each contour line corresponds to points in the domain where the function has a constant value. For a function of two variables written as z = f(x,y), a level curve is defined by the equation f(x,y) = k,...

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Related Experiment Video

Updated: Jul 7, 2026

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
14:14

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

Published on: April 16, 2017

B-spline snakes: a flexible tool for parametric contour detection.

P Brigger1, J Hoeg, M Unser

  • 1Biomedical Engineering and Instrumentation Program, National Center for Research Resources, National Institutes of Health, Bethesda, MD 20892, USA. patrick@brigger.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 12, 2008
PubMed
Summary

This study introduces a new B-spline snake formulation for efficient contour outlining. The novel method simplifies parameter optimization and enhances stability in noisy images, achieving performance comparable to traditional snakes.

Related Experiment Videos

Last Updated: Jul 7, 2026

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
14:14

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

Published on: April 16, 2017

Area of Science:

  • Computer Vision
  • Image Analysis
  • Computational Geometry

Background:

  • Traditional snake models, while effective for contour outlining, suffer from slow convergence and complex parameter tuning due to numerous control points and internal energy regularization.
  • Cubic splines are theoretically optimal for curvature-constrained snakes, but their practical implementation in traditional snake formulations presents challenges.

Purpose of the Study:

  • To develop a novel B-spline snake formulation that overcomes the limitations of traditional methods, offering faster and more intuitive contour outlining.
  • To eliminate the need for explicit internal energies by adjusting the spline's intrinsic scale a priori, simplifying the optimization process.

Main Methods:

  • A new B-spline snake formulation is proposed, adjusting the intrinsic scale of the spline model a priori.
  • This approach implicitly controls spline elasticity by varying knot spacing, reducing the number of parameters for optimization.
  • The method is integrated into a multiresolution framework to improve stability in noisy image environments.

Main Results:

  • The proposed B-spline snake formulation demonstrates comparable performance to traditional snakes that utilize internal energies.
  • The new method offers simplified parameter optimization and intuitive control over spline elasticity.
  • Improved stability in noisy image environments was observed due to the multiresolution formulation.

Conclusions:

  • The novel B-spline snake formulation provides an efficient and intuitive tool for contour outlining, particularly in biomedical applications.
  • By eliminating internal energies and adjusting knot spacing, the method simplifies snake model implementation and optimization.
  • The approach shows promise for versatile applications requiring robust and fast image segmentation.