{"title":"熵图像阈值技术综述","authors":"L. Mahmoudi, A. El Zaart","doi":"10.1109/ICTEA.2012.6462867","DOIUrl":null,"url":null,"abstract":"Entropy-based image thresholding has received considerable interest in recent years. It is an important concept in the area of image segmentation. The entropy-based approach was used to get the threshold of image from 80 ages; it is used to weight the amount of reserved information of image after segmentation. Our contribution in this paper, is to explain the idea of Shannon entropy and how he utilized it in image thresholding concept, then how it used in the idea of the cross entropy by Kullback and the concept of fuzzy entropy. We study different existing entropy algorithms for image thresholding. In this study we categorize these several algorithms into three groups according to the information they are exploiting and indicate their differences or similarities.","PeriodicalId":245530,"journal":{"name":"2012 2nd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"A survey of entropy image thresholding techniques\",\"authors\":\"L. Mahmoudi, A. El Zaart\",\"doi\":\"10.1109/ICTEA.2012.6462867\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Entropy-based image thresholding has received considerable interest in recent years. It is an important concept in the area of image segmentation. The entropy-based approach was used to get the threshold of image from 80 ages; it is used to weight the amount of reserved information of image after segmentation. Our contribution in this paper, is to explain the idea of Shannon entropy and how he utilized it in image thresholding concept, then how it used in the idea of the cross entropy by Kullback and the concept of fuzzy entropy. We study different existing entropy algorithms for image thresholding. In this study we categorize these several algorithms into three groups according to the information they are exploiting and indicate their differences or similarities.\",\"PeriodicalId\":245530,\"journal\":{\"name\":\"2012 2nd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 2nd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTEA.2012.6462867\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 2nd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTEA.2012.6462867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Entropy-based image thresholding has received considerable interest in recent years. It is an important concept in the area of image segmentation. The entropy-based approach was used to get the threshold of image from 80 ages; it is used to weight the amount of reserved information of image after segmentation. Our contribution in this paper, is to explain the idea of Shannon entropy and how he utilized it in image thresholding concept, then how it used in the idea of the cross entropy by Kullback and the concept of fuzzy entropy. We study different existing entropy algorithms for image thresholding. In this study we categorize these several algorithms into three groups according to the information they are exploiting and indicate their differences or similarities.