Anjan Dutta2012
Proceedings
2012
21st International Conference on Pattern Recognition
1663-1666
Anjan Dutta
Jaume Gibert
Josep Llados
Horst Bunke
Umapada Pal
ICPR
Combination of Product Graph and Random Walk Kernel for Symbol Spotting in Graphical Documents
This paper explores the utilization of product graph for spotting symbols on graphical documents. Product graph is intended to find the candidate subgraphs or components in the input graph containing the paths similar to the query graph. The acute angle between two edges and their length ratio are considered as the node labels. In a second step, each of the candidate subgraphs in the input graph is assigned with a distance measure computed by a random walk kernel. Actually it is the minimum of the distances of the component to all the components of the model graph. This distance measure is then used to eliminate dissimilar components. The remaining neighboring components are grouped and the grouped zone is considered as a retrieval zone of a symbol similar to the queried one. The entire method works online, i.e., it doesn't need any preprocessing step. The present paper reports the initial results of the method, which are very encouraging.