Edge detection of images using artificial bee colony algorithm
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Keywords:
Edge Detection, Artificial Bee Colony Algorithm, Digital Image Processing, Canny, Hybrid FiltersAbstract
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.
References
Deniz Yelmenoğlu, E. and Akhan Baykan, N., "Edge detection of aerial images using artificial bee colony algorithm", 10 (1): 73–80 (2022).
Owotogbe, J. S., Ibiyemi, T. S., and Adu, B. A., "Edge Detection Techniques on Digital Images-A Review", (2019).
Banharnsakun, A., "Artificial bee colony algorithm for enhancing image edge detection", Evolving Systems, 10 (4): 679–687 (2019).
Ebrahimnejad, A., Enayattabr, M., Motameni, H., and Garg, H., "Modified artificial bee colony algorithm for solving mixed interval-valued fuzzy shortest path problem", Complex And Intelligent Systems, 7 (3): 1527–1545 (2021).
Xu, Y., Fan, P., and Yuan, L., "A simple and efficient artificial bee colony algorithm", Mathematical Problems In Engineering, 2013: (2013).
Yigitbasi, E., "Edge Detection using Artificial Bee Colony Algorithm (ABC)", International Journal Of Information And Electronics Engineering, (2013).
Moussa, M., Guedri, W., and Douik, A., "A novel metaheuristic algorithm for edge detection based on artificial bee colony technique", Traitement Du Signal, 37 (3): 405–412 (2020).
Verma, O. P., Agrawal, N., and Sharma, S., "An Optimal Edge Detection Using Modified Artificial Bee Colony Algorithm", Proceedings Of The National Academy Of Sciences India Section A - Physical Sciences, 86 (2): 157–168 (2016).
Liu, Y., Institute of Electrical and Electronics Engineers, and IEEE Circuits and Systems Society, "An Application of Artificial Bee Colony Optimization to Image Edge Detection", .
Abraham, A., "A Novel Approach to Image Edge Enhancement Using Artificial Bee Colony Optimization Algorithm for Hybridized Smoothening Filters", IEEE, (2009).
Saveetha Engineering College and Institute of Electrical and Electronics Engineers, "Hybridized Approach of Artificial Bee Colony Algorithm for Detection of Suspicious Brain Pattern Using Magnetic Resonance Images", .
Li, Q., Institute of Electrical and Electronics Engineers, and IEEE Engineering in Medicine and Biology Society, "Application of Image Segmentation Based on the Artificial Bee Colony Algorithm in Fire Detection of Mine Belt Conveyor", .
Deng, Y. and Duan, H., "Biological edge detection for UCAV via improved artificial bee colony and visual attention", Aircraft Engineering And Aerospace Technology, 86 (2): 138–146 (2014).
Aslan, S., "Modified artificial bee colony algorithms for solving multiple circle detection problem", Visual Computer, 37 (4): 843–856 (2021).
