Abstract— Edge detection methods in the field of image processing are an important application area. Currently, image processing is being exploited in many areas. For this reason, methods used in developing more and more every day and studies which is about computer vision systems are being developed for less errors. Optimization algorithms have been used for better results in so many studies. In this paper, Artificial Bee Colony (ABC) Optimization Algorithm is used for edge detection which is about gray scale images. First, ABC algorithm is explained. Following, edge detection and edge detection with ABC algorithm are clarified. Finally, results are showed. Results show that the proposed method can be applied for edge detection operations.
Index Terms— Image processing, edge detection methods, meta-heuristic methods, artificial bee colony (ABC) optimization.
Elif Deniz Yigitbasi is with Işık University, Department of Computer Engineering, Istanbul, Turkiye (deniz.yigitbasi@isikun.edu.tr). Nurdan Akhan Baykan is with Selçuk University, Department of Computer Engineering, Konya, Turkiye (nurdan@selcuk.edu.tr).
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Cite: Elif Deniz Yigitbasi and Nurdan Akhan Baykan, " Edge Detection using Artificial Bee Colony Algorithm (ABC)," International Journal of Information and Electronics Engineering vol. 3, no. 6, pp. 634-638, 2013.
