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Recursive binary dilation and erosion using digital line structuring elements in arbitrary orientations.

D Nadadur1, R M Haralick

  • 1Ultrasound Group, Siemens Medical Systems, Inc., Issaquah, WA 98027-7002, USA. dnadadur@sqi.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 8, 2008
PubMed
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This study introduces efficient constant-time algorithms for binary image dilation and erosion using long line structuring elements. These methods significantly speed up morphological operations compared to brute-force approaches.

Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Geometry

Background:

  • Morphological operations like dilation and erosion are fundamental in image processing.
  • Brute-force computation with long line structuring elements is computationally intensive.
  • Existing algorithms may not offer optimal speed for various line orientations and lengths.

Purpose of the Study:

  • To develop computationally efficient, constant-time algorithms for binary image dilation and erosion.
  • To handle very long line structuring elements across all orientations.
  • To improve upon existing methods in terms of speed and performance.

Main Methods:

  • Introduced two-pass algorithms for dilation and erosion operating in constant time.
  • Utilized the concept of orientation error for digital line structuring elements.

Related Experiment Videos

  • Employed maximum/minimum operations and thresholding for transform generation.
  • Tested algorithms on noisy images with varying structuring element lengths and orientations.

    • Main Results:

    • Achieved constant-time performance for dilation and erosion with long line structuring elements.
    • Demonstrated significant speed-up (up to 100x) compared to brute-force methods.
    • Outperformed existing algorithms (Soille et al.), achieving a 4x speed-up for transform generation.
    • Algorithms are effective for various orientations and lengths of structuring elements.

    Conclusions:

    • The proposed two-pass algorithms offer a computationally efficient solution for morphological operations with long line structuring elements.
    • These algorithms provide substantial performance gains in image processing tasks.
    • The method is robust and performs better than previously published approaches.