Document image retrieval through word shape coding.
Identifieur interne : 000B18 ( Main/Exploration ); précédent : 000B17; suivant : 000B19Document image retrieval through word shape coding.
Auteurs : Shijian Lu [Singapour] ; Linlin Li ; Chew Lim TanSource :
- IEEE transactions on pattern analysis and machine intelligence [ 1939-3539 ] ; 2008.
English descriptors
- KwdEn :
- Artificial Intelligence, Automatic Data Processing (methods), Database Management Systems, Databases, Factual, Documentation (methods), Image Enhancement (methods), Image Interpretation, Computer-Assisted (methods), Information Storage and Retrieval (methods), Language, Pattern Recognition, Automated (methods), Reading.
- MESH :
Abstract
This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.
DOI: 10.1109/TPAMI.2008.89
PubMed: 18787240
Affiliations:
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Le document en format XML
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The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.</div></front></TEI><affiliations><list><country><li>Singapour</li></country></list><tree><noCountry><name sortKey="Li, Linlin" sort="Li, Linlin" uniqKey="Li L" first="Linlin" last="Li">Linlin Li</name><name sortKey="Tan, Chew Lim" sort="Tan, Chew Lim" uniqKey="Tan C" first="Chew Lim" last="Tan">Chew Lim Tan</name></noCountry><country name="Singapour"><noRegion><name sortKey="Lu, Shijian" sort="Lu, Shijian" uniqKey="Lu S" first="Shijian" last="Lu">Shijian Lu</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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