{"title":"蓝图图像二值化的自适应阈值方法","authors":"Mansuo Zhao, Hong Yan","doi":"10.1109/ISSPA.1999.815824","DOIUrl":null,"url":null,"abstract":"This paper describes a method to threshold blueprint images based on geometrical features. Scanned blueprint images often contain a lot of noise, which was produced in the process when the original map was printed on the blue paper and smudged due to long time storage. To remove the noise and extract the lines and numbers are a difficult task. We propose a new method which utilizes geometrical features combined with gray level analysis to threshold the blueprint image. The result shows a good performance compared with Otsu's (1979) method, Nilblack's method and other methods.","PeriodicalId":302569,"journal":{"name":"ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Adaptive thresholding method for binarization blueprint images\",\"authors\":\"Mansuo Zhao, Hong Yan\",\"doi\":\"10.1109/ISSPA.1999.815824\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a method to threshold blueprint images based on geometrical features. Scanned blueprint images often contain a lot of noise, which was produced in the process when the original map was printed on the blue paper and smudged due to long time storage. To remove the noise and extract the lines and numbers are a difficult task. We propose a new method which utilizes geometrical features combined with gray level analysis to threshold the blueprint image. The result shows a good performance compared with Otsu's (1979) method, Nilblack's method and other methods.\",\"PeriodicalId\":302569,\"journal\":{\"name\":\"ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPA.1999.815824\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPA.1999.815824","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive thresholding method for binarization blueprint images
This paper describes a method to threshold blueprint images based on geometrical features. Scanned blueprint images often contain a lot of noise, which was produced in the process when the original map was printed on the blue paper and smudged due to long time storage. To remove the noise and extract the lines and numbers are a difficult task. We propose a new method which utilizes geometrical features combined with gray level analysis to threshold the blueprint image. The result shows a good performance compared with Otsu's (1979) method, Nilblack's method and other methods.