Efficient Sketch Recognition Based on Shape Features and Multidimensional Indexing

Conference paper

DOI: 10.1007/978-3-319-59162-9_17

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 578)
Cite this paper as:
Buoncompagni S., Franco A., Maio D. (2018) Efficient Sketch Recognition Based on Shape Features and Multidimensional Indexing. In: Kurzynski M., Wozniak M., Burduk R. (eds) Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017. CORES 2017. Advances in Intelligent Systems and Computing, vol 578. Springer, Cham


Face sketch recognition on real forensic mug shot photo galleries is a complex task since a large amount of images needs to be matched in few seconds to produce a useful outcome. Several effective solutions for sketch-based subject identification have been recently proposed, but the cost of linear search makes them not scalable when large databases have to be scanned. In this work we propose an approach which combines the use of efficient shape features for sketch-photo matching with a suitable indexing structure based on dimensionality reduction. The proposed method provides a preliminary set of candidate photos to be used as input for the final identification based on state-of-the-art techniques, offering scalability and time efficiency without noticeably compromising recognition accuracy, as confirmed by the experimental results.

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Simone Buoncompagni
    • 1
  • Annalisa Franco
    • 1
  • Dario Maio
    • 1
  1. 1.C.d.L. Ingegneria e Scienze InformaticheUniversity of BolognaCesena (FC)Italy

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