Interactive Image Segmentation via Adaptive Weighted Distances (PREPRINT)

Abstract

An interactive algorithm for soft segmentation of natural images is presented in this paper. The user first roughly scribbles different regions of interest, and from them the whole image is automatically segmented. This soft segmentation is obtained via fast, linear complexity, computation of weighted distances to the user-provided scribbles. The adaptive weights are obtained from a series of Gabor filters, and are automatically computed according to the ability of each single filter to discriminate between the selected regions of interest. We present the underlying framework and examples showing the capability of the algorithm to segment diverse images.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2006
Accession Number
ADA478644

Entities

People

  • Alexis Protiere
  • Guillermo Sapiro

Organizations

  • University of Minnesota

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Automatic
  • Boundaries
  • Computations
  • Computer Vision
  • Equations
  • Filters
  • Image Processing
  • Image Segmentation
  • Luminance
  • Mathematical Analysis
  • Mathematics
  • Minnesota
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Segmented

Readers

  • Database Systems and Applications
  • Graph Algorithms and Convex Optimization.
  • Image Processing and Computer Vision.