DocumentCode :
3488893
Title :
Deformable HOG-Based Shape Descriptor
Author :
Almazan, Jon ; Fornes, Alicia ; Valveny, Ernest
Author_Institution :
Dept. Cienc. de la Computacio, Univ. Autonoma de Barcelona, Barcelona, Spain
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
1022
Lastpage :
1026
Abstract :
In this paper we deal with the problem of recognizing handwritten shapes. We present a new deformable feature extraction method that adapts to the shape to be described, dealing in this way with the variability introduced in the handwriting domain. It consists in a selection of the regions that best define the shape to be described, followed by the computation of histograms of oriented gradients-based features over these points. Our results significantly outperform other descriptors in the literature for the task of hand-drawn shape recognition and handwritten word retrieval.
Keywords :
feature extraction; gradient methods; handwriting recognition; handwritten character recognition; image retrieval; shape recognition; deformable HOG-based shape descriptor; deformable feature extraction method; hand-drawn shape recognition; handwritten shape recognition problem; handwritten word retrieval; histogram of oriented gradient-based feature computation; Feature extraction; Handwriting recognition; Histograms; Partitioning algorithms; Robustness; Shape; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
ISSN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2013.205
Filename :
6628770
Link To Document :
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