Dictionary Based Image Segmentation

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We propose a method for weakly supervised segmentation
of natural images, which may contain both textured or non-textured
regions. Our texture representation is based on a dictionary of image
patches. To divide an image into separated regions with similar texture
we use an implicit level sets representation of the curve, which makes
our method topologically adaptive. In addition, we suggest a multi-label
version of the method. Finally, we improve upon a similar texture representation,
by formulating the computation of a texture probability in
terms of a matrix multiplication. This results in an efficient implementation
of our segmentation method. We experimentally validated our
approach on a number of natural as well as composed images.
Original languageEnglish
Title of host publicationImage Analysis : 19th Scandinavian Conference, SCIA 2015 Copenhagen, Denmark, June 15–17, 2015 Proceedings
Number of pages12
PublisherSpringer Science+Business Media
Publication date2015
ISBN (Print)978-3-319-19664-0
ISBN (Electronic)978-3-319-19665-7
Publication statusPublished - 2015
Event19th Scandinavian Conference on Image Analysis - Copenhagen, Denmark
Duration: 15 Jun 201517 Jun 2015
Conference number: 19


Conference19th Scandinavian Conference on Image Analysis
Internet address
SeriesLecture Notes in Computer Science

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