{"title":"图像数据的自动最佳阈值分割","authors":"J. Hrubeš, J. Kozumplík","doi":"10.1109/RADIOELEK.2007.371466","DOIUrl":null,"url":null,"abstract":"This paper deals with automatic image thresholding based on fuzzy entropy definition. It is used to select the fuzzy region of membership function so that an image is able to be transformed into fuzzy domain with maximum fuzzy entropy. Then we are able to divide the fuzzy region and establish the thresholds. For selection of optimal membership function is used genetic algorithm.","PeriodicalId":446406,"journal":{"name":"2007 17th International Conference Radioelektronika","volume":"34 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Automatic Optimal Thresholding of Image Data\",\"authors\":\"J. Hrubeš, J. Kozumplík\",\"doi\":\"10.1109/RADIOELEK.2007.371466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with automatic image thresholding based on fuzzy entropy definition. It is used to select the fuzzy region of membership function so that an image is able to be transformed into fuzzy domain with maximum fuzzy entropy. Then we are able to divide the fuzzy region and establish the thresholds. For selection of optimal membership function is used genetic algorithm.\",\"PeriodicalId\":446406,\"journal\":{\"name\":\"2007 17th International Conference Radioelektronika\",\"volume\":\"34 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 17th International Conference Radioelektronika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADIOELEK.2007.371466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 17th International Conference Radioelektronika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADIOELEK.2007.371466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper deals with automatic image thresholding based on fuzzy entropy definition. It is used to select the fuzzy region of membership function so that an image is able to be transformed into fuzzy domain with maximum fuzzy entropy. Then we are able to divide the fuzzy region and establish the thresholds. For selection of optimal membership function is used genetic algorithm.