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Yayın Saliency detection with hybrid artificial bee colony-firefly optimization method(ICCESEN, 2018-12-28) Yelmenoğlu, Elif Deniz; Çelebi, Numan; Taşçı, Tuğrul; Akkurt, İskender; Günoğlu, Kadir; Akyıldırım, HakanImplementation of optimization algorithms in image processing is a quite common area of research. Detecting salient fields in images can be used for problems such as object recognition, image segmentation or video tracking problems. This case makes the determination of saliency an important factor in image processing. The algorithms developed for salient region detection are divided into two approaches as bottom-up and top-down. The bottom-up techniques determine salient regions according to the data, and the top-down techniques discover these regions by the learning of visual information of a certain object. This paper presents an optimization technique for bottom-up saliency detection algorithm based on Hybrid Artificial Bee Colony- Firefly algorithm.Yayın Edge detection using artificial bee colony algorithm (ABC)(IACSIT, 2013-11-21) Yiğitbaşı, Elif Deniz; Akhan Baykan, NurdanEdge 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.
