{"title":"Adapting the artificial bee colony metaheuristic to optimize image multilevel thresholding","authors":"Mariem Miledi, S. Dhouib","doi":"10.1109/WSCNIS.2015.7368298","DOIUrl":null,"url":null,"abstract":"The main idea of this paper is to adapt the Artificial Bee Colony metaheuristic to solve the problem of multilevel thresholding for image segmentation. More precisely, this method is exploited to optimize two maximizing functions namely the between-class variance (the Otsu's function) and the entropy thresholding (the Kapur's function). This leads, respectively, to two versions of the ABC metaheuristic: the ABC-Otsu and the ABC-Kapur. The robustness and proficiency of these two thresholding algorithms are demonstrated by applying them on a set of well-known benchmark images. Furthermore, the experimental results show the efficiency of these two thresholding methods.","PeriodicalId":253256,"journal":{"name":"2015 World Symposium on Computer Networks and Information Security (WSCNIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 World Symposium on Computer Networks and Information Security (WSCNIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSCNIS.2015.7368298","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The main idea of this paper is to adapt the Artificial Bee Colony metaheuristic to solve the problem of multilevel thresholding for image segmentation. More precisely, this method is exploited to optimize two maximizing functions namely the between-class variance (the Otsu's function) and the entropy thresholding (the Kapur's function). This leads, respectively, to two versions of the ABC metaheuristic: the ABC-Otsu and the ABC-Kapur. The robustness and proficiency of these two thresholding algorithms are demonstrated by applying them on a set of well-known benchmark images. Furthermore, the experimental results show the efficiency of these two thresholding methods.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
