Performance Analysis of Canny Edge Detector and Laplacian of Gaussian Edge Detector Algorithms

Authors

  • Umesh Dahal Bhaktapur Multiple Campus, Tribhuvan University
  • Nawaraj Paudel Central Department of Computer Science and Information Technology, Tribhuvan University
  • Jagdish Bhatta Department of Computer Science, Tribhuvan University

DOI:

https://doi.org/10.3126/oimjoc.v1i1.82547

Keywords:

Canny Edge Detector, LoG Edge Detector, Image Gradient, Kernel, Convolution, Sobel Operator, Prewitt's Operator, Gaussian Smoothing

Abstract

The core of image processing lies from the principal to represent the digital image in signals of 2-3 dimensions and applying the techniques of digital signal processing to obtain the diverse parameters related to image. Edge detection is the preprocessing techniques of image processing which includes mathematical methods that aims in identifying the sharp discontinuities in an image. The theme of this article is particularized on the performance analysis among Canny Edge Detection and Laplacian of Gaussian (LoG) Edge Detection algorithms on behalf of their execution time. The result in this study shows that the performance of LoG Edge detection algorithm is better than the performance of Canny Edge detection algorithm on the basis of their execution time.

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Published

2025-08-05

How to Cite

Dahal, U., Paudel, N., & Bhatta, J. (2025). Performance Analysis of Canny Edge Detector and Laplacian of Gaussian Edge Detector Algorithms. Orchid Insights: A Multidisciplinary Journal of Orchid College, 1(1), 48–54. https://doi.org/10.3126/oimjoc.v1i1.82547

Issue

Vol. 1 No. 1 (2025)

Section

Articles

License

Copyright (c) 2025 The Author(s)

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