A bag-of-paths based serialized subgraph matching for symbol spotting in line drawings
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
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
Bag-of-GraphPaths descriptors for symbol recognition and spotting in line drawings
GREC'11 Proceedings of the 9th international conference on Graphics Recognition: new trends and challenges
Automatic analysis and sketch-based retrieval of architectural floor plans
Pattern Recognition Letters
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In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes.