{"title":"An Algorithm for Histogram Median Thresholding","authors":"A. Bosakova-Ardenska, A. Danev","doi":"10.1145/3274005.3274019","DOIUrl":null,"url":null,"abstract":"One algorithm for thresholding using a histogram median is presented in this paper. The algorithm is named HisMedian and it is implemented on Java. It is also proposed a taxonomy of thresholding algorithms based on a method for defining threshold value as a real color of image or calculated color's value. According to the proposed taxonomy a set of popular thresholding algorithms (including HisMedian) is experimentally evaluated using three test images. The experimental results show that if a histogram is bimodal then the algorithms which use real color(s) from the image as a threshold(s) achieve better results than algorithms which use calculated value(s) as a threshold(s).","PeriodicalId":152033,"journal":{"name":"Proceedings of the 19th International Conference on Computer Systems and Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 19th International Conference on Computer Systems and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3274005.3274019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
One algorithm for thresholding using a histogram median is presented in this paper. The algorithm is named HisMedian and it is implemented on Java. It is also proposed a taxonomy of thresholding algorithms based on a method for defining threshold value as a real color of image or calculated color's value. According to the proposed taxonomy a set of popular thresholding algorithms (including HisMedian) is experimentally evaluated using three test images. The experimental results show that if a histogram is bimodal then the algorithms which use real color(s) from the image as a threshold(s) achieve better results than algorithms which use calculated value(s) as a threshold(s).