TY  - CHAP
AU  - Klaus Broelemann
AU  - Anjan Dutta
AU  - Xiaoyi Jiang
AU  - Josep Llados
ED  - Bart Lamiroy
ED  - Jean-Marc Ogier
PY  - 2014//
TI  - Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents
T2  - LNCS
BT  - Graphics Recognition. Current Trends and Challenges
SP  - 25
EP  - 37
VL  - 8746
PB  - Springer Berlin Heidelberg
N2  - Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance. But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result, the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset.
SN  - 0302-9743
SN  - 978-3-662-44853-3
L1  - http://refbase.cvc.uab.es/files/BDJ2014.pdf
UR  - http://dx.doi.org/10.1007/978-3-662-44854-0_3
N1  - DAG; 600.045; 600.056; 600.061; 600.077
ID  - Klaus Broelemann2014
ER  -