@inproceedings{2c20c4ecced1466c82b58822430339d9,
title = "Clustering algorithm optimized by brain storm optimization for digital image segmentation",
abstract = "In the last several decades digital images were extend their usage in numerous areas. Due to various digital image processing methods they became part areas such as astronomy, agriculture and more. One of the main task in image processing application is segmentation. Since segmentation represents rather important problem, various methods were proposed in the past. One of the methods is to use clustering algorithms which is explored in this paper. We propose k-means algorithm for digital image segmentation. K-means algorithm's well known drawback is the high possibility of getting trapped into local optima. In this paper we proposed brain storm optimization algorithm for optimizing k-means algorithm used for digital image segmentation. Our proposed algorithm is tested on several benchmark images and the results are compared with other stat-of-the-art algorithms. The proposed method outperformed the existing methods.",
keywords = "Clustering, Digital image processing, Machine learning, Optimization, Segmentation, Swarm intelligence",
author = "Eva Tuba and Raka Jovanovic and Dejan Zivkovic and Marko Beko and Milan Tuba",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 7th International Symposium on Digital Forensics and Security, ISDFS 2019 ; Conference date: 10-06-2019 Through 12-06-2019",
year = "2019",
month = jun,
doi = "10.1109/ISDFS.2019.8757552",
language = "English",
series = "7th International Symposium on Digital Forensics and Security, ISDFS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Asaf Varol and Murat Karabatak and Cihan Varol and Sevginur Teke",
booktitle = "7th International Symposium on Digital Forensics and Security, ISDFS 2019",
address = "United States",
}