Deformable Mesh Evolved by Similarity of Image Patches

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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 languageEnglish
Title of host publicationProceedings of 2019 IEEE International Conference on Image Processing
PublisherIEEE
Publication date2019
Pages2731-2735
ISBN (Print)978-1-5386-6249-6
DOIs
Publication statusPublished - 2019
Event2019 IEEE International Conference on Image Processing - Taipei International Convention Center, Taipei, Taiwan, Province of China
Duration: 22 Sep 201929 Sep 2019

Conference

Conference2019 IEEE International Conference on Image Processing
LocationTaipei International Convention Center
CountryTaiwan, Province of China
CityTaipei
Period22/09/201929/09/2019

Keywords

  • Textured segmentation
  • Adaptive triangle mesh
  • Mumford-Shah

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