Canny Edge Detector

The Canny Edge Detector is a computational method in image processing that identifies edges by detecting sharp changes in image intensity through a multi-stage algorithm incorporating noise reduction, gradient calculation, non-maximum suppression, and hysteresis thresholding.

1.1K

Publications

42.5K

Citations

3.2K

Authors

1K

Institutions

Publications per year

2017–2026

428

Authors

3.2K

  1. KW
    Kevin W. Bowyer

    University of Notre Dame, United States

    6 publications · 1.4K citations

    6

    h-index

  2. PS
    Palaiahnakote Shivakumara

    University of Malaya, Malaysia

    5 publications · 176 citations

    5

    h-index

  3. AB
    Abdullah Bade

    Universiti of Malaysia Sabah, Malaysia

    4 publications · 148 citations

    4

    h-index

  4. DD
    Didier Demigny

    École Nationale Supérieure de l'Électronique et de ses Applications, France

    4 publications · 279 citations

    4

    h-index

  5. MH
    Mohd Hanafi Ahmad Hijazi

    Universiti of Malaysia Sabah, Malaysia

    4 publications · 148 citations

    4

    h-index

1–5 of 3.2K

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 17 publications · 3.3K citations

    16

    h-index

  2. Remote Sensing

    16 publications · 715 citations

    15

    h-index

  3. IEEE Access

    19 publications · 802 citations

    15

    h-index

  4. Procedia Computer Science

    14 publications · 592 citations

    13

    h-index

  5. 12

    h-index

1–5