Skip to Main content Skip to Navigation
Conference papers

Symbol descriptor based on shape context and vector model of information retrieval

Thi Oanh Nguyen 1 Salvatore Tabbone 1 Oriol Ramos Terrades 1
1 QGAR - Querying Graphics through Analysis and Recognition
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : In this paper we present an adaptative method for graphic symbol representation based on shape contexts. The proposed descriptor is invariant under classical geometric transforms (rotation, scale) and based on interest points. To reduce the complexity of matching a symbol to a large set of candidates we use the popular vector model for information retrieval. In this way, on the set of shape descriptors we build a visual vocabulary where each symbol is retrieved on visual words. Experimental results on complex and occluded symbols show that the approach is very promising.
Complete list of metadata

Cited literature [20 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00334432
Contributor : Thi Oanh Nguyen Connect in order to contact the contributor
Submitted on : Sunday, October 26, 2008 - 12:35:12 PM
Last modification on : Tuesday, May 18, 2021 - 3:32:05 PM
Long-term archiving on: : Monday, June 7, 2010 - 6:48:48 PM

File

nguyen-symbolDescriptor-scip.p...
Files produced by the author(s)

Identifiers

Collections

Citation

Thi Oanh Nguyen, Salvatore Tabbone, Oriol Ramos Terrades. Symbol descriptor based on shape context and vector model of information retrieval. The 8th IAPR International Workshop on Document Analysis Systems, Sep 2008, Nara, Japan. pp.191-197, ⟨10.1109/DAS.2008.58⟩. ⟨hal-00334432⟩

Share

Metrics

Record views

643

Files downloads

696