Interactive segmentation of multiple images

Yan Nei Law*, Hwee Kuan Lee, Kwok Po Ng, Andy M. Yip

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

In this paper, we propose an optimization model for interactive segmentation of multiple images. The user marks some sample pixels or objects in one or more images. Then, the method employs the samples as strong priors to automatically segment other input images. A good feature of the method is that the segmentation is highly controllable by the user, so that the user can easily obtain the kind of objects that he/she wants. The approach is especially effective for segmentation of a large collection of images that share similar features, where the user inputs some samples once and for all. We demonstrate the usefulness of the model to the segmentation of various collections of bioimages.

Original languageEnglish
Title of host publicationProceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Pages571-575
Number of pages5
Publication statusPublished - 2011
Event2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 - Las Vegas, NV, United States
Duration: 18 Jul 201121 Jul 2011

Publication series

NameProceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Volume2

Conference

Conference2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011
Country/TerritoryUnited States
CityLas Vegas, NV
Period18/07/1121/07/11

Scopus Subject Areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

User-Defined Keywords

  • Bioimage segmentation
  • Image segmentation
  • Interactive
  • Microscopy images
  • Multiple images

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