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Breadth-first search and its application to image processing problems.

J Silvela1, J Portillo

  • 1Nortel Networks, Madrid, Spain. jsilvela@nortelnetworks.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 breadth-first graph traversal algorithms for digital image processing tasks like region erosion and dilation. These methods optimize memory usage and processing speed by focusing on relevant pixels.

Area of Science:

  • Computer Vision
  • Image Processing
  • Graph Theory

Background:

  • Digital image processing often requires efficient algorithms for region manipulation.
  • Traditional methods may involve complete image scans, impacting performance and memory.
  • Graph traversal offers a novel framework for image analysis.

Purpose of the Study:

  • To explore the application of breadth-first graph traversal in digital image processing.
  • To develop efficient algorithms for common image region operations.
  • To improve memory efficiency and processing speed for these operations.

Main Methods:

  • Utilized breadth-first graph traversal for region processing.
  • Implemented algorithms for erosion, dilation, skeletonization, and distance transformation.

Related Experiment Videos

  • Employed a queue to manage unprocessed pixels, ensuring efficient traversal.

    • Main Results:

    • Developed memory-efficient algorithms that process only relevant pixels and their neighbors.
    • Achieved faster processing by avoiding complete image scans.
    • Demonstrated the effectiveness of breadth-first traversal for image region manipulation.

    Conclusions:

    • Breadth-first graph traversal provides an efficient framework for digital image processing.
    • The proposed algorithms offer significant improvements in memory and speed.
    • This approach enhances the processing of regions in digital images.