NDLI: Texture synthesis: textons revisited

Content Provider	IEEE Xplore Digital Library
Author	Charalampidis, D.
Copyright Year	1992
Abstract	This paper introduces a technique for synthesizing natural textures, with emphasis on quasiperiodic and structural textures. Textures are assumed to be composed of three components, namely illumination, structure, and stochastic. The contribution of this work is that, in contrast to previous techniques, it proposes a joint approach for handling the texture's global illumination, irregular structure, and stochastic component which may be correlated to the other two components. Furthermore, the proposed technique does not produce verbatim copies in the synthesized texture. More specifically, a top-down approach is used for extraction of texture elements (textons) in which, in contrast to previous texton-based approaches, no assumptions regarding perfect periodicity are made. The structure itself can be modeled as a stochastic process. Consequently, textons are allowed to have irregular and nonidentical shapes. In the synthesis stage, a new nonregular textural structure is designed from the original one that defines the place holders for textons. We call such place holders empty textons (e-textons). The e-textons are filled in by a representative texton. Since e-textons do not have identical shapes, a texton shape-matching procedure is required. After adding the illumination to the structural component, a strictly localized version of a block sampling technique is applied to add the stochastic component. The block sampling technique combined with the addition of the illumination component provides a significant improvement in the appearance of synthesized textures. Results show that the proposed method is successful in synthesizing structural textures visually indistinguishable to the original. Moreover, the method is successful in synthesizing a variety of stochastic textures.
Sponsorship	IEEE Signal Processing Society
Page Count	11
File Size	4156166
Starting Page	777
Ending Page	787
File Format	PDF
ISSN	10577149
Volume Number	15
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Lighting Spatial resolution Shape Sampling methods Application software Predictive models Image segmentation Computer applications Computer vision texture synthesis Periodicity detection textons
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A random set view of texture classification

Integrating intensity and texture differences for robust change detection

Segmentation of textured images using a multiresolution Gaussian autoregressive model

Image segmentation and analysis via multiscale gradient watershed hierarchies

EdgeFlow: a technique for boundary detection and image segmentation

Boundary localization in texture segmentation

Multiresolution Gauss-Markov random field models for texture segmentation

Image Retargeting by Texture-Aware Synthesis

Adaptive scale fixing for multiscale texture segmentation

Texture synthesis: textons revisited

Similar Documents

A random set view of texture classification

Integrating intensity and texture differences for robust change detection

Segmentation of textured images using a multiresolution Gaussian autoregressive model

Image segmentation and analysis via multiscale gradient watershed hierarchies

EdgeFlow: a technique for boundary detection and image segmentation

Boundary localization in texture segmentation

Multiresolution Gauss-Markov random field models for texture segmentation

Image Retargeting by Texture-Aware Synthesis

Adaptive scale fixing for multiscale texture segmentation

Texture synthesis: textons revisited