Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/40091
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dc.titleSimilarity measure for CCITT group 4 compressed document images
dc.contributor.authorLu, Y.
dc.contributor.authorTan, C.L.
dc.contributor.authorFan, L.
dc.contributor.authorHuang, W.
dc.date.accessioned2013-07-04T07:56:27Z
dc.date.available2013-07-04T07:56:27Z
dc.date.issued2001
dc.identifier.citationLu, Y.,Tan, C.L.,Fan, L.,Huang, W. (2001). Similarity measure for CCITT group 4 compressed document images. IEEE International Conference on Image Processing 1 : 1118-1121. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40091
dc.description.abstractSimilarity measure of document images acts a crucial role in the area of document image retrieval. A method of measuring the similarity of CCITT Group 4 compressed document images is proposed in this paper. The features are extracted directly from the changing elements of the compressed images. Weighted Hausdorff distance is utilized to assign all of the word objects from two document images to corresponding classes by an unsupervised classifier, whereas the possible stop words are excluded. Document vectors are built by the occurrence frequency of the word object classes, and the pair-wise similarity of two document images is represented by the scalar product of the document vectors. Five group articles relating to different domains are used to test the validity of the presented approach.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleIEEE International Conference on Image Processing
dc.description.volume1
dc.description.page1118-1121
dc.description.coden85QTA
dc.identifier.isiutNOT_IN_WOS
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