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A systolic algorithm for Euclidean distance transform.

Masafumi Miyazawa1, Peifeng Zeng, Naoyuki Iso

  • 1Brother Industries, Ltd., 3-17-1, osu, naka-ku, Nagoya, Japan. miyazawa@nuee.nagoya-u.ac.jp

IEEE Transactions on Pattern Analysis and Machine Intelligence
|June 24, 2006
PubMed
Summary

This study introduces a novel systolic algorithm for computing Euclidean distance maps in binary images. The efficient algorithm reduces hardware needs, avoiding multipliers for easier VLSI implementation.

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Area of Science:

  • Computer Science
  • Image Processing
  • Algorithm Design

Background:

  • The Euclidean distance transform is a core image processing technique.
  • It finds applications in computer vision, pattern recognition, and robotics.

Purpose of the Study:

  • To propose a novel systolic algorithm for Euclidean distance map computation.
  • To achieve efficient hardware implementation with reduced resources.

Main Methods:

  • Development of a systolic algorithm for N x N binary images.
  • Algorithm designed for 3N clock cycles and 2N^2 processing cells.
  • Focus on minimizing hardware complexity, specifically avoiding multipliers.

Main Results:

  • The proposed algorithm computes the Euclidean distance map in 3N clock cycles.

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  • It utilizes 2N^2 processing cells.
  • The design eliminates the need for multipliers, simplifying VLSI implementation.

    • Conclusions:

    • The developed systolic algorithm offers an efficient method for Euclidean distance map computation.
    • The algorithm's resource-efficient design, particularly the absence of multipliers, facilitates VLSI implementation.
    • This contributes to advancements in hardware-accelerated image processing and computer vision applications.