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Recursive erosion, dilation, opening, and closing transforms.

S Chen1, R M Haralick

  • 1Dept. of Electr. Eng., Washington Univ., Seattle, WA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1995
PubMed
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New recursive morphological transforms (RET, RDT, ROT, RCT) enable constant-time image processing per pixel. These novel transforms efficiently compute erosions, dilations, openings, and closings for all structuring element sizes simultaneously.

Area of Science:

  • Digital Image Processing
  • Computer Vision
  • Morphological Image Analysis

Background:

  • Morphological operations are fundamental in image processing.
  • Traditional methods face challenges with varying structuring element sizes.
  • Efficient computation is crucial for real-time vision tasks.

Purpose of the Study:

  • Introduce novel recursive morphological transforms.
  • Address limitations of existing morphological operations.
  • Enable efficient computation for complex image analysis tasks.

Main Methods:

  • Developed recursive erosion transform (RET) and recursive dilation transform (RDT).
  • Developed recursive opening transform (ROT) and recursive closing transform (RCT).
  • Analyzed computational complexity for pixel-wise operations.

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Main Results:

  • Transforms compute erosions, dilations, openings, and closings in constant time per pixel.
  • RET and RDT achieve N+2 operations per pixel.
  • ROT and RCT achieve 14N operations per pixel (experimental).

Conclusions:

  • Recursive morphological transforms offer significant computational advantages.
  • These transforms provide efficient solutions for vision tasks requiring adaptive structuring element sizes.
  • The methods enhance the efficiency of digital image processing pipelines.