{"title":"(半)自动识别水中微生物","authors":"K. Rodenacker, P. Gais, U. Jütting, B. Hense","doi":"10.1109/ICIP.2001.958043","DOIUrl":null,"url":null,"abstract":"The structure of biocenosis is a powerful indicator for the condition of and changes in the quality of the ecosystem. Identification and quantification of populations of microorganisms enables an assessment of the effect of any stressor on it. A method and some results are presented using automatic image acquisition, evaluation and recognition to ease the time consuming part of manual organism recognition and counting at the microscope.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"(Semi-)automatic recognition of microorganisms in water\",\"authors\":\"K. Rodenacker, P. Gais, U. Jütting, B. Hense\",\"doi\":\"10.1109/ICIP.2001.958043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The structure of biocenosis is a powerful indicator for the condition of and changes in the quality of the ecosystem. Identification and quantification of populations of microorganisms enables an assessment of the effect of any stressor on it. A method and some results are presented using automatic image acquisition, evaluation and recognition to ease the time consuming part of manual organism recognition and counting at the microscope.\",\"PeriodicalId\":291827,\"journal\":{\"name\":\"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2001.958043\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2001.958043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
(Semi-)automatic recognition of microorganisms in water
The structure of biocenosis is a powerful indicator for the condition of and changes in the quality of the ecosystem. Identification and quantification of populations of microorganisms enables an assessment of the effect of any stressor on it. A method and some results are presented using automatic image acquisition, evaluation and recognition to ease the time consuming part of manual organism recognition and counting at the microscope.