PT Unknown
AU Pau Riba
   Josep Llados
   Alicia Fornes
TI Error-tolerant coarse-to-fine matching model for hierarchical graphs
BT 11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
PY 2017
BP 107
EP 117
VL 10310
DI 10.1007/978-3-319-58961-9
DE Graph  matching; Hierarchical  graph; Graph-based  representation; Coarse-to-fine matching
AB Graph-based  representations  are  effective  tools  to  capture structural information from visual elements. However, retrieving a query graph  from  a  large  database  of  graphs  implies  a  high  computational complexity. Moreover, these representations are very sensitive to noise or small changes. In this work, a novel hierarchical graph representation is designed. Using graph clustering techniques adapted from graph-based social  media  analysis,  we propose  to  generate a  hierarchy  able  to  deal with different levels of abstraction while keeping information about the topology.  For  the  proposed  representations,  a  coarse-to-fine  matching method is defined. These approaches are validated using real scenarios such as classification of colour images and handwritten word spotting.
ER