PT Unknown
AU Sergio Escalera
   Alicia Fornes
   Oriol Pujol
   Alberto Escudero
   Petia Radeva
TI Circular Blurred Shape Model for Symbol Spotting in Documents
BT 16th IEEE International Conference on Image Processing
PY 2009
BP 1985
EP 1988
AB Symbol spotting problem requires feature extraction strategies able to generalize from training samples and to localize the target object while discarding most part of the image. In the case of document analysis, symbol spotting techniques have to deal with a high variability of symbols' appearance. In this paper, we propose the Circular Blurred Shape Model descriptor. Feature extraction is performed capturing the spatial arrangement of significant object characteristics in a correlogram structure. Shape information from objects is shared among correlogram regions, being tolerant to the irregular deformations. Descriptors are learnt using a cascade of classifiers and Abadoost as the base classifier. Finally, symbol spotting is performed by means of a windowing strategy using the learnt cascade over plan and old musical score documents. Spotting and multi-class categorization results show better performance comparing with the state-of-the-art descriptors.
ER