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Related Concept Videos

Downsampling01:20

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
Reducing Line Loss01:18

Reducing Line Loss

In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
Unsymmetric Loading of Thin-Walled Members01:23

Unsymmetric Loading of Thin-Walled Members

Thin-walled members with non-symmetrical cross-sections are vital to engineering structures, offering material efficiency and structural integrity. However, unsymmetrical loading on these members leads to complex stress distributions, resulting in simultaneous bending and twisting can cause deformation or structural failure. The interaction between bending and twisting requires detailed analysis to ensure structural resilience.
The concept of the shear center is crucial in countering the...
Fast Fourier Transform01:10

Fast Fourier Transform

The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
Unsymmetric Loading of Thin-Walled Members: Problem Solving01:07

Unsymmetric Loading of Thin-Walled Members: Problem Solving

The shear center of a channel section with uniform thickness, height, and width, is determined by computing the shear force in the member and calculating the moments of inertia of the sections.
To compute the shear forces, find the shear flow at a specific distance from the endpoint using the vertical shear and the moment of inertia values. The total shear force on the flange is calculated by integrating the shear flow from one end of the flange to the other.
Next, calculate the moments of...

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Thinned-skull Cortical Window Technique for In Vivo Optical Coherence Tomography Imaging
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Thinned-skull Cortical Window Technique for In Vivo Optical Coherence Tomography Imaging

Published on: November 19, 2012

A width-independent fast thinning algorithm.

C Arcelli1, G S Di Baja

  • 1Istituto di Cibernetica, C.N.R., 80072 Arco Felice, Naples, Italy.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient digital image thinning algorithm to create skeletons, reducing data and simplifying analysis. The method speeds up processing and generates well-shaped, topologically sound skeletons.

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Area of Science:

  • Digital Image Processing
  • Computational Geometry

Background:

  • Digital figure skeletons offer data reduction and simplified analysis.
  • Conventional thinning methods are computationally intensive.

Purpose of the Study:

  • To develop a faster and more efficient digital figure thinning algorithm.
  • To produce well-shaped skeletons with preserved topological properties.

Main Methods:

  • Image cleaning and pixel labeling based on distance from background.
  • Topology-preserving operations to create a linear structure.
  • Pruning of irrelevant branches for domain-specific applications.

Main Results:

  • A novel thinning procedure significantly speeds up skeletonization.
  • The resulting skeletons exhibit correct connectedness, topology, and shape.
  • The original figure can be reconstructed using reverse distance transformation.

Conclusions:

  • The proposed algorithm offers a computationally modest and efficient approach to skeletonization.
  • The method is particularly advantageous for wider digital figures.
  • The generated skeletons are suitable for description and classification tasks.