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Multiresolution analysis in extraction of reference lines from documents with gray level background
Tang Y.Y.2; Ma H.3; Liu J.1; Li B.F.1; Xi D.1
1997-12-01
Source PublicationIEEE Transactions on Pattern Analysis and Machine Intelligence
ISSN01628828
Volume19Issue:8Pages:921-926
Abstract

Based on wavelets, a new theoretical method has been developed to process multi-gray level documents. In this method, two-dimensional multiresolution analysis, wavelet decomposition algorithm, and compactly supported orthonormal wavelets are used to transform a document image into sub-images. According to these sub-images, the reference lines of a multi-gray level document can be extracted, and knowledge about the geometric structure of the document can be acquired. Particularly, this approach is more efficient to process form documents with gray level background. Experiments indicate that this new method can be applied to process documents with promising results. ©1997 IEEE.

KeywordCompactly Supported Orthonormal Wavelets Document Analysis Sub-image Two-dimensional Multiresolution Analysis Wavelet Decomposition Algorithm Wavelets
DOI10.1109/34.608296
URLView the original
Language英語English
WOS IDWOS:A1997XT98700012
Scopus ID2-s2.0-0031212798
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Citation statistics
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Sichuan University
2.Hong Kong Baptist University
3.Universite Concordia
Recommended Citation
GB/T 7714
Tang Y.Y.,Ma H.,Liu J.,et al. Multiresolution analysis in extraction of reference lines from documents with gray level background[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(8), 921-926.
APA Tang Y.Y.., Ma H.., Liu J.., Li B.F.., & Xi D. (1997). Multiresolution analysis in extraction of reference lines from documents with gray level background. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(8), 921-926.
MLA Tang Y.Y.,et al."Multiresolution analysis in extraction of reference lines from documents with gray level background".IEEE Transactions on Pattern Analysis and Machine Intelligence 19.8(1997):921-926.
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