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Edge-detection schemes highly suitable for hardware implementation.

L Basano1, B Caprile, E De Micheli

  • 1Dipartimento di Fisica, Università di Genova, Italy.

Journal of the Optical Society of America. A, Optics and Image Science
|July 1, 1988
PubMed
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This study introduces efficient edge detection algorithms for real images using gradient maxima. Simple filters, like binary or 4-bit, offer satisfactory performance and are ideal for hardware implementation.

Area of Science:

  • Computer Vision
  • Image Processing
  • Digital Signal Processing

Background:

  • Edge detection is crucial for image analysis.
  • Existing methods can be computationally intensive.
  • Efficient hardware implementation is desired for real-time applications.

Purpose of the Study:

  • To present two novel edge detection schemes for real images.
  • To enable efficient hardware implementation of edge detection algorithms.
  • To demonstrate that simple filters achieve satisfactory performance.

Main Methods:

  • Edge detection based on gradient maxima.
  • Image filtering using narrow filters to enhance localization.
  • Evaluation of binary and 4-bit finite-impulse-response (FIR) filters.

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Main Results:

  • The exact filter shape is not critical for algorithm performance.
  • Binary and 4-bit filters allow for highly efficient hardware implementation.
  • Performance is comparable to more sophisticated edge detection schemes.

Conclusions:

  • Low-cost edge detection schemes using simple filters are suitable for hardware implementation.
  • These methods offer a practical alternative to complex algorithms.
  • Efficient hardware implementation can be achieved without sacrificing performance.