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Related Experiment Video

Updated: May 29, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Optimal Edge Detector Design II: Coefficient Quantization.

W H Lunscher1, M P Beddoes

  • 1Research and Development Division, Develcon Electronics Limited, Saskatoon. Canada.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary

This study proposes a method for selecting the minimum coefficient word size for digital edge detection filters. This ensures accurate edge localization in images, even with noise, by meeting specific performance bounds.

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Last Updated: May 29, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Area of Science:

  • Image Processing
  • Digital Signal Processing
  • Computer Vision

Background:

  • Edge detection is crucial for image analysis.
  • Laplacian of Gaussian (LoG) filters are effective for edge localization via zero crossings.
  • Filter accuracy is influenced by noise and filter parameters.

Purpose of the Study:

  • To propose a method for determining the minimum coefficient word size for digital LoG filters.
  • To ensure accurate edge detection in digital implementations.
  • To satisfy in-band rejection bounds for direct-form filter implementations.

Main Methods:

  • Analysis of the sampled LoG filter.
  • Development of a method for coefficient word size selection.
  • Focus on direct-form filter implementation.

Main Results:

  • A method for selecting minimum coefficient word size was proposed.
  • The method aims to satisfy in-band rejection bounds.
  • This addresses challenges in digital filter implementation.

Conclusions:

  • The proposed method facilitates efficient and accurate digital implementation of LoG edge detection filters.
  • Optimizing coefficient word size is key for performance in noisy conditions.
  • This contributes to robust image processing techniques.