{"title":"灰度滤波的线和词分割","authors":"Yi Lu, A. Tisler","doi":"10.1109/ICDAR.1995.601979","DOIUrl":null,"url":null,"abstract":"The extraction of lines, words and characters from a digital document image are necessary computational steps preceding character recognition. Much has been discussed in character segmentation and recognition but little has been done in the area of line and word segmentation. The authors present two special filters, minimum difference filters (MDF) and average difference filters (ADF) to facilitate line and word segmentation. They discuss how to select the scales of these filters dynamically and how to use the filters to eliminate crossing lines from a text image.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"159 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Gray scale filtering for line and word segmentation\",\"authors\":\"Yi Lu, A. Tisler\",\"doi\":\"10.1109/ICDAR.1995.601979\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The extraction of lines, words and characters from a digital document image are necessary computational steps preceding character recognition. Much has been discussed in character segmentation and recognition but little has been done in the area of line and word segmentation. The authors present two special filters, minimum difference filters (MDF) and average difference filters (ADF) to facilitate line and word segmentation. They discuss how to select the scales of these filters dynamically and how to use the filters to eliminate crossing lines from a text image.\",\"PeriodicalId\":273519,\"journal\":{\"name\":\"Proceedings of 3rd International Conference on Document Analysis and Recognition\",\"volume\":\"159 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd International Conference on Document Analysis and Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.1995.601979\",\"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 of 3rd International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.1995.601979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gray scale filtering for line and word segmentation
The extraction of lines, words and characters from a digital document image are necessary computational steps preceding character recognition. Much has been discussed in character segmentation and recognition but little has been done in the area of line and word segmentation. The authors present two special filters, minimum difference filters (MDF) and average difference filters (ADF) to facilitate line and word segmentation. They discuss how to select the scales of these filters dynamically and how to use the filters to eliminate crossing lines from a text image.