A symbol spotting approach in graphical documents by hashing serialized graphs
Pattern Recognition
On the use of geometric matching for both: isolated symbol recognition and symbol spotting
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
Building a symbol library from technical drawings by identifying repeating patterns
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
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This paper addresses the difficult problem of symbol spotting for graphic documents. We propose an approach where each graphic document is indexed as a text document by using the vector model and an inverted file structure. The method relies on a visual vocabulary built from a shape descriptor adapted to the document level and invariant under classical geometric transforms (rotation, scaling and translation). Regions of interest selected with high degree of confidence using a voting strategy are considered as occurrences of a query symbol. Experimental results are promising and show the feasibility of our approach.