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International Conference on Computer Analysis of Images and Patterns

CAIP 2017: Computer Analysis of Images and Patterns pp 190–201Cite as

Indexing of Single and Multi-instance Iris Data Based on LSH-Forest and Rotation Invariant Representation

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10425))

Abstract

Indexing of iris data is required to facilitate fast search in large-scale biometric systems. Previous works addressing this issue were challenged by the tradeoffs between accuracy, computational efficacy, storage costs, and maintainability. This work presents an iris indexing approach based on rotation invariant iris representation and LSH-Forest to produce an accurate and easily maintainable indexing structure. The complexity of insertion or deletion in the proposed method is limited to the same logarithmic complexity of a query and the required storage grows linearly with the database size. The proposed approach was extended into a multi-instance iris indexing scheme resulting in a clear performance improvement. Single iris indexing scored a hit rate of 99.7% at a 0.1% penetration rate while multi-instance indexing scored a 99.98% hit rate at the same penetration rate. The evaluation of the proposed approach was conducted on a large database of 50k references and 50k probes of the left and the right irises. The advantage of the proposed solution was put into prospective by comparing the achieved performance to the reported results in previous works.

This work was supported by the German Federal Ministry of Education and Research (BMBF) as well as by the Hessen State Ministry for Higher Education, Research and the Arts (HMWK) within CRISP.

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Author information

Authors and Affiliations

  1. Fraunhofer Institute for Computer Graphics Research (IGD), Darmstadt, Germany

    Naser Damer, Philipp Terhörst, Andreas Braun & Arjan Kuijper

  2. Physics Department, Technische Universität Darmstadt, Darmstadt, Germany

    Philipp Terhörst

  3. Mathematical and Applied Visual Computing, Technische Universität Darmstadt, Darmstadt, Germany

    Arjan Kuijper

Authors
  1. Naser Damer
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  2. Philipp Terhörst
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  3. Andreas Braun
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  4. Arjan Kuijper
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Corresponding author

Correspondence to Naser Damer .

Editor information

Editors and Affiliations

  1. Linköping University, Linköping, Sweden

    Michael Felsberg

  2. Lund University, Lund, Sweden

    Anders Heyden

  3. University of Southern Denmark, Odense, Denmark

    Norbert Krüger

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Damer, N., Terhörst, P., Braun, A., Kuijper, A. (2017). Indexing of Single and Multi-instance Iris Data Based on LSH-Forest and Rotation Invariant Representation. In: Felsberg, M., Heyden, A., Krüger, N. (eds) Computer Analysis of Images and Patterns. CAIP 2017. Lecture Notes in Computer Science(), vol 10425. Springer, Cham. https://doi.org/10.1007/978-3-319-64698-5_17

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  • DOI: https://doi.org/10.1007/978-3-319-64698-5_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64697-8

  • Online ISBN: 978-3-319-64698-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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