{"title":"扫描噪声的表征及纹理特征分析的量化","authors":"G. Martín, M. Pattichis","doi":"10.1109/IAI.2004.1300964","DOIUrl":null,"url":null,"abstract":"The study of the effects of scanning on texture features is of great interest to computer-based screening systems. A mathematical model is developed for understanding how the original image gets distorted due to the contrast variability and geometric distortion inherent in the scanning process. Both quantitative and qualitative results (for sixty common texture features) are given.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The characterization of scanning noise and quantization on texture feature analysis\",\"authors\":\"G. Martín, M. Pattichis\",\"doi\":\"10.1109/IAI.2004.1300964\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The study of the effects of scanning on texture features is of great interest to computer-based screening systems. A mathematical model is developed for understanding how the original image gets distorted due to the contrast variability and geometric distortion inherent in the scanning process. Both quantitative and qualitative results (for sixty common texture features) are given.\",\"PeriodicalId\":326040,\"journal\":{\"name\":\"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAI.2004.1300964\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAI.2004.1300964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The characterization of scanning noise and quantization on texture feature analysis
The study of the effects of scanning on texture features is of great interest to computer-based screening systems. A mathematical model is developed for understanding how the original image gets distorted due to the contrast variability and geometric distortion inherent in the scanning process. Both quantitative and qualitative results (for sixty common texture features) are given.