{"title":"文本分割自动文档处理","authors":"Dinesh P. Mital, Goh Wee Leng","doi":"10.1016/S0745-7138(05)80036-3","DOIUrl":null,"url":null,"abstract":"<div><p>There is a considerable interest in designing automatic systems that can scan a given paper document and store it on electronic media for easier storage, manipulation and access. Most documents contain graphics and images, in addition to text. Thus, the document image has to be segmented to identify text and image regions, so that appropriate techniques may be applied to those regions. In this paper, we have presented a new technique for image segmentation in which text and image regions, in a given document image, are automatically identified. The technique is based on the differential-processing text extraction concept. The proposed technique is capable of analysing complex document image layouts. The document image is processed by using textural feature analysis. Results of the proposed method are presented with test images which demonstrate the robustness of the technique.</p></div>","PeriodicalId":100806,"journal":{"name":"Journal of Microcomputer Applications","volume":"18 4","pages":"Pages 375-392"},"PeriodicalIF":0.0000,"publicationDate":"1995-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0745-7138(05)80036-3","citationCount":"0","resultStr":"{\"title\":\"Text segmentation for automatic document processing\",\"authors\":\"Dinesh P. Mital, Goh Wee Leng\",\"doi\":\"10.1016/S0745-7138(05)80036-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>There is a considerable interest in designing automatic systems that can scan a given paper document and store it on electronic media for easier storage, manipulation and access. Most documents contain graphics and images, in addition to text. Thus, the document image has to be segmented to identify text and image regions, so that appropriate techniques may be applied to those regions. In this paper, we have presented a new technique for image segmentation in which text and image regions, in a given document image, are automatically identified. The technique is based on the differential-processing text extraction concept. The proposed technique is capable of analysing complex document image layouts. The document image is processed by using textural feature analysis. Results of the proposed method are presented with test images which demonstrate the robustness of the technique.</p></div>\",\"PeriodicalId\":100806,\"journal\":{\"name\":\"Journal of Microcomputer Applications\",\"volume\":\"18 4\",\"pages\":\"Pages 375-392\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S0745-7138(05)80036-3\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Microcomputer Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0745713805800363\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Microcomputer Applications","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0745713805800363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Text segmentation for automatic document processing
There is a considerable interest in designing automatic systems that can scan a given paper document and store it on electronic media for easier storage, manipulation and access. Most documents contain graphics and images, in addition to text. Thus, the document image has to be segmented to identify text and image regions, so that appropriate techniques may be applied to those regions. In this paper, we have presented a new technique for image segmentation in which text and image regions, in a given document image, are automatically identified. The technique is based on the differential-processing text extraction concept. The proposed technique is capable of analysing complex document image layouts. The document image is processed by using textural feature analysis. Results of the proposed method are presented with test images which demonstrate the robustness of the technique.