Texture segmentation using a diffusion region growing technique

doi:10.1016/0031-3203(90)90104-S

Pattern Recognition

Volume 23, Issue 9, 1990, Pages 953-960

https://doi.org/10.1016/0031-3203(90)90104-S Get rights and content

Abstract

In this paper we consider the segmentation of textured images using a diffusion region growing method. This method is able to grow several separate (but similar) regions simultaneously, and is very well suited to parallel implementation. Recent research, both in computer and human vision, suggests the use of spatial/spatial-frequency (s/sf) image representations as the basis for such tasks. The representation we have used is an approximation to the Wigner distribution, an s/sf representation that has recently been suggested as corresponding to the early and preattentive stage of visual processing. Experimental results on both synthesized and natural textures are shown.

References (24)

H. Wechsler
texture analysis—a survey
Signal Process.
(1980)
L. Van Gool et al.
Texture analysis anno 1983
Comput. Vision Graphics Image Process.
(1985)
A.B. Watson
The cortex transform: rapid computation of simulated neural images
Comput. Vision Graphics Image Process.
(1987)
J. Beck et al.
Spatial frequency channels and perceptual grouping in texture segregation
Comput. Vision Graphics Image Process.
(1987)
L. Jacobson et al.
A paradigm for invariant object recognition of brightness, optical flow and binocular disparity images
Pattern Recognition Lett.
(1982)
L. Jacobson et al.
Derivation of optical flow using a spatiotemporal-frequency approach
Comput. Vision Graphics Image Process.
(1987)
L. Jacobson et al.
Joint spatial/spatial-frequency representation
Signal Process.
(1988)
T.R. Reed et al.
Tracking of non-stationarities for texture fields
Signal Process.
(1988)
R.M. Haralick
Statistical image texture analysis
E.M. Gurari et al.
On the difficulties involved in the segmentation of pictures
IEEE Trans. Pattern Anal. Mach. Intell.
(1982)

T. R. Reed and H. Wechsler, Segmentation of textured images and Gestalt organization using spatial/spatial-frequency...

F.H.C. Crick et al.

An Information Processing Approach to Understanding the Visual Cortex

M.I.T. A.I. memo 557

(1980)

Cited by (0)

View full text

Texture segmentation using a diffusion region growing technique

Abstract

Signal Process.

Comput. Vision Graphics Image Process.

Comput. Vision Graphics Image Process.

Comput. Vision Graphics Image Process.

Pattern Recognition Lett.

Comput. Vision Graphics Image Process.

Signal Process.

Signal Process.

Statistical image texture analysis

On the difficulties involved in the segmentation of pictures

IEEE Trans. Pattern Anal. Mach. Intell.

An Information Processing Approach to Understanding the Visual Cortex

M.I.T. A.I. memo 557