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Dynamic Selection Feature Extractor for Trademark Retrieval

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Advances in Soft Computing (MICAI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11288))

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Abstract

The paper contributes to the CBIR systems applied to trademark retrieval. The proposed method seeks to find dynamically the best feature extractor that represents the trademark queried. In the experiments are applied four feature extractors: Concavity/Convexity deficiencies (CC), Freeman Chain (FC), Scale Invariant Feature Transform (SIFT) and Hu Invariant Moments (Hu). These extractors represent a set of classes of features extractors, which are submitted to a classification process using two different classifiers: ANN (Artificial Neural Networks) and SVM (Support Vector Machines). The selecting the best feature extractor is important to processing the next levels in search of similar trademarks (i.e. applying zoning mechanisms or combining the best feature extractors), because it is possible restrict the number of operations in large databases. We carried out experiments using UK Patent Office database, with 10,151 images. Our results are in the same basis of the literature and the average in the best case for the normalized recall (Rn) is equal to 0.91. Experiments show that dynamic selection of extractors can contribute to improve the trademarks retrieval.

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Acknowledgments

The authors wish to thanks the CAPES, Federal Technological University of Parana (UTFPR-PG, Brazil) and Pontifical Catholic University of Parana (PUCPR, Brazil), which have supported this work.

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Authors and Affiliations

  1. Universidade Tecnológica Federal do Paraná, Ponta Grossa, Paraná, Brazil

    Simone B. K. Aires & Mauren L. Sguario

  2. Pontifícia Universidade Católica do Paraná, Curitiba, Paraná, Brazil

    Cinthia O. A. Freitas

Authors
  1. Simone B. K. Aires
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  2. Cinthia O. A. Freitas
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  3. Mauren L. Sguario
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Corresponding authors

Correspondence to Simone B. K. Aires or Cinthia O. A. Freitas .

Editor information

Editors and Affiliations

  1. Instituto Politécnico Nacional, Mexico City, Mexico

    Ildar Batyrshin

  2. Universidad Panamericana, Mexico City, Mexico

    María de Lourdes Martínez-Villaseñor

  3. Faculty of Engineering, Universidad Panamericana, Mexico City, Mexico

    Hiram Eredín Ponce Espinosa

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Aires, S.B.K., Freitas, C.O.A., Sguario, M.L. (2018). Dynamic Selection Feature Extractor for Trademark Retrieval. In: Batyrshin, I., Martínez-Villaseñor, M., Ponce Espinosa, H. (eds) Advances in Soft Computing. MICAI 2018. Lecture Notes in Computer Science(), vol 11288. Springer, Cham. https://doi.org/10.1007/978-3-030-04491-6_17

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  • DOI: https://doi.org/10.1007/978-3-030-04491-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04490-9

  • Online ISBN: 978-3-030-04491-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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