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Relation Bag-of-Features for Symbol Retrieval

Santosh K.C. 1 Laurent Wendling 2 Bart Lamiroy 3 
1 READ - Recognition of writing and analysis of documents
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
3 QGAR - Querying Graphics through Analysis and Recognition
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : In this paper, we address a new scheme for symbol retrieval based on relation bag-of-features (BOFs) which are computed between the extracted visual primitives. Our feature consists of pairwise spatial relations from all possible combina tions of individual visual primitives. The key characteristic of the overall process is to use topological information to guide directional relations. Consequently, directional relation matching takes place only with those candidates having similar topological configurations. A comprehensive study is made by using two different datasets. Experimental tests provide interesting results by establishing user-friendly symbol retrieval application.
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Submitted on : Monday, May 20, 2013 - 2:57:53 AM
Last modification on : Wednesday, October 27, 2021 - 2:40:01 PM
Long-term archiving on: : Tuesday, April 4, 2017 - 8:30:16 AM


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  • HAL Id : hal-00823960, version 1


Santosh K.C., Laurent Wendling, Bart Lamiroy. Relation Bag-of-Features for Symbol Retrieval. ICDAR - International Conference on Document Analysis and Recognition - 2013, Aug 2013, Washington DC, United States. ⟨hal-00823960⟩



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