NDLI: Texel-based texture segmentation

Content Provider	IEEE Xplore Digital Library
Author	Todorovic, S. Ahuja, N.
Copyright Year	2009
Description	Author affiliation: Beckman Institute, University of Illinois at Urbana-Champaign, USA (Ahuja, N.) \|\| School of EECS, Oregon State University, USA (Todorovic, S.)
Abstract	Given an arbitrary image, our goal is to segment all distinct texture subimages. This is done by discovering distinct, cohesive groups of spatially repeating patterns, called texels, in the image, where each group defines the corresponding texture. Texels occupy image regions, whose photometric, geometric, structural, and spatial-layout properties are samples from an unknown pdf. If the image contains texture, by definition, the image will also contain a large number of statistically similar texels. This, in turn, will give rise to modes in the pdf of region properties. Texture segmentation can thus be formulated as identifying modes of this pdf. To this end, first, we use a low-level, multiscale segmentation to extract image regions at all scales present. Then, we use the meanshift with a new, variable-bandwidth, hierarchical kernel to identify modes of the pdf defined over the extracted hierarchy of image regions. The hierarchical kernel is aimed at capturing texel substructure. Experiments demonstrate that accounting for the structural properties of texels is critical for texture segmentation, leading to competitive performance vs. the state of the art.
Starting Page	841
Ending Page	848
File Size	2965791
Page Count	8
File Format	PDF
ISBN	9781424444205
ISSN	15505499
DOI	10.1109/ICCV.2009.5459308
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-29
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Layout Photometry Kernel Surface texture Shape Optical materials Lighting Bandwidth Optical variables control
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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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
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