𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Texture classification method using multiple space filling curves

✍ Scribed by Jia-Hong Lee; Yuang-Cheh Hsueh


Publisher
Elsevier Science
Year
1994
Tongue
English
Weight
894 KB
Volume
15
Category
Article
ISSN
0167-8655

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Clustering algorithm using space filling
✍ Mostafa Mjahed πŸ“‚ Article πŸ“… 2003 πŸ› Elsevier Science 🌐 English βš– 278 KB

According to a space filling curve, distances between points in a multidimensional space are replaced by distances along a Lebesgue measure-preserving curve. By using a neighbouring approach on the space filling curve, several clusters may emerge fkom data and configurations may be associated to the

Lossless compression of medical images u
✍ Jan-Yie Liang; Chih-Sheng Chen; Chua-Huang Huang; Li Liu πŸ“‚ Article πŸ“… 2008 πŸ› Elsevier Science 🌐 English βš– 723 KB

A Hilbert space-filling curve is a curve traversing the 2 n Γ— 2 n two-dimensional space and it visits neighboring points consecutively without crossing itself. The application of Hilbert space-filling curves in image processing is to rearrange image pixels in order to enhance pixel locality. A compu

Thin absorbers using space-filling curve
✍ John McVay; Ahmad Hoorfar; Nader Engheta πŸ“‚ Article πŸ“… 2009 πŸ› John Wiley and Sons 🌐 English βš– 508 KB

## Abstract Following our previous work, here an artificial magnetic conducting (AMC) surface, comprised of Hilbert and/or Peano space‐filling curve inclusions is utilized as a thin electromagnetic absorber. Numerical results are presented to show the effects of the incident angle, conducting strip

Image texture classification using wavel
✍ Srinivasan Ramakrishnan; Srinivasan Selvan πŸ“‚ Article πŸ“… 2007 πŸ› John Wiley and Sons 🌐 English βš– 262 KB

## Abstract This article describes a new approach for image texture classification based on curve fitting of wavelet domain singular values and probabilistic neural networks. Image textures are wavelet packet transformed and singular value decomposition is then employed on subband coefficient matri