Edge detection of images using artificial bee colony algorithm


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Authors

  • Mohamed Al Tawil Karabük University
  • Omar Dakkak Karabük University

Keywords:

Edge Detection, Artificial Bee Colony Algorithm, Digital Image Processing, Canny, Hybrid Filters

Abstract

Digital image pre-processing is of great importance today due to the development of technology in several areas, the most important of which are medical and military. Edge detection is one of the most important and popular pre-processing techniques because it has many benefits in removing unimportant information and extracting accurate and important information in images. It is considered as the sudden change in intensity between adjacent pixels. To date, edge detection of images complicated by noise or lack of data is still under development. For this, many algorithms and methods have been used, and an attempt is made to improve them by combining them with other methods and algorithms to improve the detection of image edges. In our research, we touched on the artificial bee colony algorithm (ABC), considered one of the optimization algorithms, as it is one of the most used methods for finding the optimal solution and has widespread in the fields of optimization. This algorithm mimics the foraging behavior of bees. We have provided some articles on ways to use this algorithm to detect the edges of digital images and show the advantages and disadvantages of each method.

Author Biographies

Mohamed Al Tawil , Karabük University

Faculty of Engineering, Department of Computer Engineering, 78050, Karabük, Turkey

Omar Dakkak, Karabük University

Faculty of Engineering, Department of Computer Engineering, 78050, Karabük, Turkey

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Published

2023-02-26

How to Cite

Al Tawil , M., & Dakkak, O. (2023). Edge detection of images using artificial bee colony algorithm. International Conference on Frontiers in Academic Research, 1, 309–315. Retrieved from https://as-proceeding.com/index.php/icfar/article/view/121