%0 Conference Proceedings
%T New Approach for Symbol Recognition Combining Shape Context of Interest Points with Sparse Representation
%A Thanh Ha Do
%A Salvatore Tabbone
%A Oriol Ramos Terrades
%B 12th International Conference on Document Analysis and Recognition
%D 2013
%@ 1520-5363
%F Thanh Ha Do2013
%O DAG
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2331), last updated on Thu, 07 Mar 2019 11:03:33 +0100
%X In this paper, we propose a new approach for symbol description. Our method is built based on the combination of shape context of interest points descriptor and sparse representation. More specifically, we first learn a dictionary describing shape context of interest point descriptors. Then, based on information retrieval techniques, we build a vector model for each symbol based on its sparse representation in a visual vocabulary whose visual words are columns in the learneddictionary. The retrieval task is performed by ranking symbols based on similarity between vector models. Evaluation of our method, using benchmark datasets, demonstrates the validity of our approach and shows that it outperforms related state-of-theart methods.
%U http://refbase.cvc.uab.es/files/DTR2013b.pdf
%U http://dx.doi.org/10.1109/ICDAR.2013.60
%P 265-269