A Survey on Various Approaches for Edge Detection

Authors

  • Saja Hikmat Dawood  Department of Computer, Collage of Basic Education, University of AL-Mustansiriyah, Baghdad, Iraq

DOI:

https://doi.org//10.32628/IJSRSET23103142

Keywords:

Edge detection, Sobel, Prewitt, Roberts, Canny, LOG, DoG, Soft computing, ANN, FL, GA.

Abstract

Edge detection is a fundamental image processing technique used to spot sudden shifts in color or intensity in image. It is utilized to detect and highlight boundaries between various items or regions in image, as well as to detect features such as corners, circles and lines. Edge detection approaches typically work by applying a filter to an image to detect areas where the image undergoes an immediate shift in magnitude. Applications for edge detection techniques include recognizing objects, healthcare images, and background segmentation. Many techniques have been presented based on the classical approaches (such as Sobel, Prewitt, and Roberts, Canny, Laplacian of Gaussian (LOG), etc.) and soft computing approaches (SCA), which are the two main approaches for detection of edge. This paper provides an overview of studies carried out on edge detection using various approaches. That will assist brand-new researchers in learning about these techniques and selecting one from among them to evolve or improve according to their field of study.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2023-06-30

Issue

Volume 10, Issue 4, July-August-2023

Section

Research Articles

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How to Cite

[1]
Saja Hikmat Dawood, " A Survey on Various Approaches for Edge Detection, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 10, Issue 4, pp.27-41, July-August-2023. Available at doi : https://doi.org/10.32628/IJSRSET23103142