Paper
16 December 1992 Parallel distributed algorithm for texture boundary localization
Stephan D. Yhann, Tzay S. Young
Author Affiliations +
Abstract
In most instances the boundaries between textured regions are defined by the gray level contrasts which result from the local interaction between the texture elements in each region. In such cases, the boundaries can be accurately characterized by gray level edge segments. Using these edge segments to localize the texture boundary directly addresses the major problem associated with texture segmentation, namely the localization verses classification accuracy conflict. The accuracy of segmentation methods which rely only on spatially distributed properties to characterize the texture, is limited to the spacial extent of the property used. In contrast, gray level edges are significantly more localized. However, before they can be of any use, the gray level edge segments defining the texture boundary must be isolated from the edges defining the texture elements. In this paper, we define a set of properties to do this. We also incorporate these properties into a parallel distributed algorithm which is used to segment a set of sample texture images.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephan D. Yhann and Tzay S. Young "Parallel distributed algorithm for texture boundary localization", Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); https://doi.org/10.1117/12.130841
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Neurons

Signal processing

Lawrencium

Stochastic processes

Image classification

Image processing

RELATED CONTENT

Hierarchical multiresolution texture image segmentation
Proceedings of SPIE (October 22 1993)
Target detection in FLIR image sequence using neural network
Proceedings of SPIE (December 16 1992)
Image segmentation using an annealed Hopfield neural network
Proceedings of SPIE (December 16 1992)
Adaptive image segmentation by quantization
Proceedings of SPIE (December 16 1992)

Back to Top