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Bit vector architecture for computational mathematical morphology.

John C Handley1

  • 1Xerox Corp., Webster, NY 14580-9701, USA. jhandley@crt.xerox.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 2, 2008
PubMed
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A novel real-time architecture for computational mathematical morphology enables efficient computation of translation-invariant nonlinear operators. This pipelined design offers fixed operational complexity and memory proportional to operator basis size.

Area of Science:

  • Computer Science
  • Image Processing
  • Digital Signal Processing

Background:

  • Computational mathematical morphology involves complex nonlinear discrete operators.
  • Existing architectures may lack efficiency for real-time applications.

Purpose of the Study:

  • To present a real-time, compact architecture for translation-invariant windowed nonlinear discrete operators.
  • To enable efficient computation and pipelining of these operators.

Main Methods:

  • Developed a three-step architecture utilizing table lookups and bitwise operations.
  • Implemented operators using vector observations as indices into bit vector tables.
  • Computed output values based on the position of the first nonzero bit.

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Main Results:

  • The proposed architecture allows output values to be computed in a fixed number of operations.
  • Memory requirements are proportional to the operator's basis size.
  • A modification allows for increasing operator complexity.

Conclusions:

  • The presented architecture offers an efficient and compact solution for real-time computational mathematical morphology.
  • The design facilitates pipelined processing, reducing computational bottlenecks.
  • This approach is suitable for applications requiring fast, translation-invariant nonlinear filtering.