Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Chaotic Dynamics

arXiv:chao-dyn/9407012 (chao-dyn)
[Submitted on 26 Jul 1994]

Title:Texture Segmentation by Local Bi-Orthogonal Decomposition

Authors:J.A. Dente, R. Vilela Mendes, R. Lima
View PDF
Abstract: We investigate the ability of a local bi-orthogonal decomposition to build texture segmentation of images. Using the structures associated to the local decomposition of the image independent row and columns we perform a segmentation, where the regions are defined by the property of having a smooth variation of the corresponding entropy. Examples are choosen in texture made and also in real life images. The size of the local analysis is also determined by the properties of the (global) bi-orthogonal decomposition.
Comments: 9 pages,CPT-94/P.3010,tex,18 fig available on this http URL directory pub/preprints/94/dynamical-systems/94-P.3010
Subjects: Chaotic Dynamics (nlin.CD)
Cite as: arXiv:chao-dyn/9407012
  (or arXiv:chao-dyn/9407012v1 for this version)
  https://doi.org/10.48550/arXiv.chao-dyn/9407012

Submission history

From: Jean-Bruno Erismann [view email]
[v1] Tue, 26 Jul 1994 14:41:18 UTC (9 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
nlin.CD
< prev   |   next >
new | recent | 1994-07

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)