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 Experiment Videos

Three processing characteristics of visual texture segmentation.

T Caelli1

  • 1Psychology Department, University of Alberta, Edmonton, Canada.

Spatial Vision
|January 1, 1985
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Object recognition and image understanding: theories of everything?

Spatial vision·2001
Same author

Learning paradigms for image interpretation.

Spatial vision·2001
Same author

Theory of spatiochromatic image encoding and feature extraction.

Journal of the Optical Society of America. A, Optics, image science, and vision·2000
Same author

The IPRS Image Processing and Pattern Recognition System.

Spatial vision·1997
Same author

A structural and relational approach to handwritten word recognition.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·1997
Same author

Visual learning of patterns and objects.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·1997
Same journal

Comment on 'angle illusion on a picture's surface' by Hammad et al. (2008).

Spatial vision·2009
Same journal

Feature-based attentional modulation increases with stimulus separation in divided-attention tasks.

Spatial vision·2009
Same journal

Spatial distance between target and irrelevant patch modulates detection in a texture segmentation task.

Spatial vision·2009
Same journal

Inhibition related impairments of coherent motion perception in the attention-induced motion blindness paradigm.

Spatial vision·2009
Same journal

Recognition units in reading: backward masking experiments.

Spatial vision·2009
Same journal

Spatial-temporal modeling of interactive image interpretation.

Spatial vision·2009
See all related articles

Researchers outline three computational mechanisms sufficient for texture segmentation and discrimination. These include convolution, nonlinear filtering (impletion), and grouping based on detector responses, offering insights into visual processing.

Area of Science:

  • Computer Vision
  • Computational Neuroscience
  • Image Processing

Background:

  • Texture segmentation and discrimination are fundamental tasks in visual perception.
  • Understanding the computational underpinnings of these processes is crucial for artificial intelligence and cognitive science.

Purpose of the Study:

  • To outline computational mechanisms sufficient for texture segmentation and discrimination.
  • To compare these mechanisms with those proposed for human visual texture perception.

Main Methods:

  • Convolution of detector profiles with the input image.
  • Nonlinear filtering (impletion) for perceptual 'filling in' of detector outputs.
  • Grouping of image areas based on differences in detector responses post-impletion.

Related Experiment Videos

Main Results:

  • Three distinct mechanisms (convolution, impletion, grouping) are identified as sufficient for texture segmentation.
  • These computational mechanisms provide a framework for analyzing visual texture processing.

Conclusions:

  • The proposed computational framework offers a potential explanation for texture segmentation and discrimination.
  • Further research can explore the parallels between these mechanisms and human visual cortex functions.