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Multiscale Edge Detection Using a Finite Element Framework for Hexagonal Pixel-Based Images.

Bryan Gardiner, Sonya A Coleman, Bryan W Scotney

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |February 19, 2016
    PubMed
    Summary

    This study introduces a novel finite element method for designing hexagonal image processing operators. The efficient linear approach enables scalable edge detection and multi-scale edge map generation for hexagonal images.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Finite Element Analysis

    Background:

    • Hexagonal pixel-based image processing is an emerging area.
    • Existing edge detection algorithms are being developed for hexagonal image structures.

    Purpose of the Study:

    • To present a novel and efficient approach for designing hexagonal image processing operators.
    • To develop scalable first-order and Laplacian operators using the finite element framework.

    Main Methods:

    • Utilizing linear basis and test functions within the finite element framework.
    • Designing hexagonal image processing operators.
    • Efficient reuse of a seven-point linear operator for multi-scale edge map generation.

    Main Results:

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    • A framework for efficient design of large-scale neighborhood operators for hexagonal images.
    • Generation of edge maps at different scales.
    • Evaluation of operator accuracy and algorithmic performance.

    Conclusions:

    • The proposed finite element approach offers an efficient method for hexagonal image processing.
    • This framework facilitates scalable operator design and multi-scale edge detection.