Abstract
In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time.
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Acknowledgment
This work has been partially supported by the People Programme (Marie Curie Actions) of the Seventh Framework Programme of the European Union (FP7/2007-2013) under REA grant agreement no. 600388, and by the Agency of Competitiveness for Companies of the Government of Catalonia, ACCIÓ; and by the Spanish Ministry of Education and Science under projects TIN2009-14633-C03-03, TIN2011-25606 and TIN2012-37475-C02-02.
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Rusiñol, M., Karatzas, D., Lladós, J. (2014). Spotting Graphical Symbols in Camera-Acquired Documents in Real Time. In: Lamiroy, B., Ogier, JM. (eds) Graphics Recognition. Current Trends and Challenges. GREC 2013. Lecture Notes in Computer Science(), vol 8746. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44854-0_1
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DOI: https://doi.org/10.1007/978-3-662-44854-0_1
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