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Related Experiment Video

Updated: Jun 1, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Collinear segment detection using HT neighborhoods.

Shengzhi Du1, Chunling Tu, Barend Jacobus van Wyk

  • 1Department of Electrical and Mining Engineering, School of Engineering, College of Science Engineering and Technology, University of South Africa, Pretoria 0003, South Africa. dushengzhi@gmail.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|May 25, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for detecting straight line segments using Hough Transform (HT) data. The approach accurately determines segment parameters without edge point verification, robustly handling collinear segments and noise.

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Last Updated: Jun 1, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

Area of Science:

  • Computer Vision
  • Image Processing
  • Geometric Analysis

Background:

  • Accurate straight line segment detection is crucial in image analysis.
  • Existing methods often rely on edge point verification, limiting robustness.
  • Distinguishing collinear segments and handling noise remain challenges.

Purpose of the Study:

  • To propose a novel method for straight line segment detection using Hough Transform (HT) features.
  • To determine complete segment parameters (center, length, slope, distance to origin) solely from HT data.
  • To enhance robustness against noise and improve discrimination of collinear segments.

Main Methods:

  • Geometrical analysis of Hough Transform (HT) peaks to extract novel straight line segment features.
  • Development of a segment detection method utilizing only HT data, avoiding image space edge point verification.
  • Derivation of a theoretical criterion for straight line contiguity to resolve collinear segments.

Main Results:

  • The proposed method successfully determines complete straight line segment parameters.
  • It demonstrates robustness to disturbing edge points, particularly collinear ones.
  • The method effectively distinguishes between highly collinear straight line segments.
  • Experimental results confirm consistent and robust performance in image processing tasks.

Conclusions:

  • A practical and robust straight line segment detection method is presented, based entirely on Hough Transform (HT) data.
  • The method overcomes limitations of edge point verification and enhances performance in cluttered or noisy images.
  • This approach offers a significant advancement for applications requiring precise straight line detection.