Please use this identifier to cite or link to this item: https://doi.org/10.1109/TPAMI.2002.1008389
DC FieldValue
dc.titleImaged document text retrieval without OCR
dc.contributor.authorTan, C.L.
dc.contributor.authorHuang, W.
dc.contributor.authorYu, Z.
dc.contributor.authorXu, Y.
dc.date.accessioned2013-07-04T07:35:52Z
dc.date.available2013-07-04T07:35:52Z
dc.date.issued2002
dc.identifier.citationTan, C.L.,Huang, W.,Yu, Z.,Xu, Y. (2002). Imaged document text retrieval without OCR. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (6) : 838-844. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/TPAMI.2002.1008389" target="_blank">https://doi.org/10.1109/TPAMI.2002.1008389</a>
dc.identifier.issn01628828
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39184
dc.description.abstractWe propose a method for text retrieval from document images without the use of OCR. Documents are segmented into character objects. Image features, namely, the Vertical Traverse Density (VTD) and Horizontal Traverse Density (HTD), are extracted. An n-gram based document vector is constructed for each document based on these features. Text similarity between documents is then measured by calculating the dot product of the document vectors. Testing with seven corpora of imaged textual documents in English and Chinese as well as images from UW1 database confirms the validity of the proposed method.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TPAMI.2002.1008389
dc.sourceScopus
dc.subjectDocument image analysis
dc.subjectDocument vector
dc.subjectText retrieval
dc.subjectText similarity
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/TPAMI.2002.1008389
dc.description.sourcetitleIEEE Transactions on Pattern Analysis and Machine Intelligence
dc.description.volume24
dc.description.issue6
dc.description.page838-844
dc.description.codenITPID
dc.identifier.isiutNOT_IN_WOS
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