Deformable Mesh Evolved by Similarity of Image Patches

Tuan T. Nguyen; Vedrana Andersen Dahl; J. Andreas Barentzen; Anders Bjorholm Dahl

doi:10.1109/icip.2019.8803264

Deformable Mesh Evolved by Similarity of Image Patches

Tuan T. Nguyen, Vedrana Andersen Dahl, J. Andreas Barentzen, Anders Bjorholm Dahl

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

We propose a deformable model for manually initialized segmentation of images, which may contain both textured and non-textured regions. Image segments and segment boundaries are represented using a deformable triangle mesh, providing all advantages of an explicit geometry representation, but allowing for adaptive topology. Deformation forces are computed using a probabilistic model of local self-similarity, based on clustering of image patches. Both our curve representation and our similarity model naturally support multi-label segmentation. We demonstrate the properties of our approach on a number of natural color images as well as composed textured images.

Original language	English
Title of host publication	Proceedings of 2019 IEEE International Conference on Image Processing
Publisher	IEEE
Publication date	2019
Pages	2731-2735
ISBN (Print)	978-1-5386-6249-6
DOIs	https://doi.org/10.1109/icip.2019.8803264
Publication status	Published - 2019
Event	2019 IEEE International Conference on Image Processing - Taipei International Convention Center, Taipei, Taiwan, Province of China Duration: 22 Sept 2019 → 25 Sept 2019 https://www.2019.ieeeicip.org/2019.ieeeicip.org/index-2.html

Conference

Conference	2019 IEEE International Conference on Image Processing
Location	Taipei International Convention Center
Country/Territory	Taiwan, Province of China
City	Taipei
Period	22/09/2019 → 25/09/2019
Internet address	https://www.2019.ieeeicip.org/2019.ieeeicip.org/index-2.html

Keywords

Textured segmentation
Adaptive triangle mesh
Mumford-Shah

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10.1109/icip.2019.8803264

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title = "Deformable Mesh Evolved by Similarity of Image Patches",

abstract = "We propose a deformable model for manually initialized segmentation of images, which may contain both textured and non-textured regions. Image segments and segment boundaries are represented using a deformable triangle mesh, providing all advantages of an explicit geometry representation, but allowing for adaptive topology. Deformation forces are computed using a probabilistic model of local self-similarity, based on clustering of image patches. Both our curve representation and our similarity model naturally support multi-label segmentation. We demonstrate the properties of our approach on a number of natural color images as well as composed textured images.",

keywords = "Textured segmentation, Adaptive triangle mesh, Mumford-Shah",

author = "Nguyen, \{Tuan T.\} and Dahl, \{Vedrana Andersen\} and Barentzen, \{J. Andreas\} and Dahl, \{Anders Bjorholm\}",

year = "2019",

doi = "10.1109/icip.2019.8803264",

language = "English",

isbn = "978-1-5386-6249-6",

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booktitle = "Proceedings of 2019 IEEE International Conference on Image Processing",

publisher = "IEEE",

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AB - We propose a deformable model for manually initialized segmentation of images, which may contain both textured and non-textured regions. Image segments and segment boundaries are represented using a deformable triangle mesh, providing all advantages of an explicit geometry representation, but allowing for adaptive topology. Deformation forces are computed using a probabilistic model of local self-similarity, based on clustering of image patches. Both our curve representation and our similarity model naturally support multi-label segmentation. We demonstrate the properties of our approach on a number of natural color images as well as composed textured images.

KW - Textured segmentation

KW - Adaptive triangle mesh

KW - Mumford-Shah

U2 - 10.1109/icip.2019.8803264

DO - 10.1109/icip.2019.8803264

M3 - Article in proceedings

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BT - Proceedings of 2019 IEEE International Conference on Image Processing

PB - IEEE

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ER -

Deformable Mesh Evolved by Similarity of Image Patches

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