PT Unknown
AU P. Wang
   V. Eglin
   C. Garcia
   C. Largeron
   Josep Llados
   Alicia Fornes
TI A Novel Learning-free Word Spotting Approach Based on Graph Representation
BT 11th IAPR International Workshop on Document Analysis and Systems
PY 2014
BP 207
EP 211
DI 10.1109/DAS.2014.46
AB Effective information retrieval on handwritten document images has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment result is introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods.
ER