Graph-cut Based Interactive Segmentation of 3D Materials-Science Images

Abstract

Abstract Segmenting materials images is a laborious and time-consuming process, and automatic image segmentation algorithms usually contain imperfections and errors. Interactive segmentation is a growing topic in the areas of image processing and computer vision, which seeks to find a balance between fully automatic methods and fully-manual segmentation processes. By allowing minimal and simplistic interaction from the user in an otherwise automatic algorithm, interactive segmentation is able to simultaneously reduce the time taken to segment an image while achieving better segmentation results. Given the specialized structure of materials images and level of segmentation quality required, we show an interactive segmentation framework for materials images that has three key contributions: (1) a multi-labeling approach that can handle a large number of structures while still quickly and conveniently allowing manual addition and removal of segments in real-time, (2) multiple extensions to the interactive toolswhich increase the simplicity of the interaction, and (3) a web interface for using the interactive tools in a client/server architecture.

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Document Details

Document Type
Technical Report
Publication Date
Apr 26, 2014
Accession Number
ADA604454

Entities

People

  • Jarrell Waggoner
  • Jeff Simmons
  • Marc De Graef
  • Song Wang
  • Youjie Zhou

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Advanced Materials
  • Artificial Intelligence
  • Biomaterials
  • Computer Science
  • Computer Vision
  • Detection
  • Detectors
  • Engineering
  • Image Processing
  • Image Segmentation
  • Machine Learning
  • Materials
  • Materials Science
  • Signal Processing
  • Supervised Machine Learning
  • Three Dimensional
  • Two Dimensional

Readers

  • Computer Vision.
  • Database Systems and Applications

Technology Areas

  • AI & ML