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Diffuse edge fitting and following: a location-adaptive approach.

A L Shipman1, R R Bitmead, G H Allen

  • 1Department of Electrical and Electronic Engineering, James Cook University of North Queensland, Townsville, Queensland, Australia.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel edge detection and tracing method for image analysis, particularly useful for noisy meteorological and physiological images. The adaptive scope technique enhances boundary detection in diffuse objects.

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Area of Science:

  • Image Analysis
  • Computer Vision
  • Pattern Recognition

Background:

  • Edge detection is crucial for image segmentation, especially in fields like meteorology and physiology.
  • Identifying boundaries in noisy or ill-defined images presents a significant challenge.

Purpose of the Study:

  • To develop an adaptive edge detection and tracing procedure for diffuse objects in images.
  • To improve boundary definition in meteorological and physiological image segmentation.

Main Methods:

  • An edge detection and line fitting procedure using an adaptive 'scope' size.
  • Predictor-corrector techniques for iterative refinement of edge tracing and confidence estimation.

Main Results:

  • The procedure successfully assigns direction, gradient measure, and fit quality to detected edges.
  • Adaptive scope adjustment enables tracing of object boundaries even with varying diffusion and noise.

Conclusions:

  • The proposed method offers robust edge detection and tracing for diffuse objects in challenging image conditions.
  • Demonstrated effectiveness on synthetic and real-world satellite meteorological images.