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A Logical Approach to the Analysis of Aerospace Images

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Perspectives of System Informatics (PSI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11964))

Abstract

The paper proposes algorithms and software tools for the automatic interpretation and classification of objects and situations on aerospace images by structural-spatial analysis and iterative reasoning based on fuzzy logic and expert rules of inference. During iterations, the decision tree is built, the transition to local rules and additional features is carried out, and the ranges of acceptable values are adjusted. Particular attention is paid to geometric features of objects. Quantitative attributes are converted to qualitative ones for ease of perception of results and forming decision rules. The results of the experiment on the automatic identification of objects in the aerial image of an urban area are given. The system is useful for automating the process of labeling images for supervised learning and testing programs that recognize objects in aerospace images.

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Acknowledgment

This work is supported by the Russian Science Foundation under grant No. 18-71-00109.

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Authors and Affiliations

  1. Kalashnikov Izhevsk State Technical University, Izhevsk, Russian Federation

    Valeriy Kuchuganov, Denis Kasimov & Aleksandr Kuchuganov

Authors
  1. Valeriy Kuchuganov
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  2. Denis Kasimov
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  3. Aleksandr Kuchuganov
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Corresponding author

Correspondence to Denis Kasimov .

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Editors and Affiliations

  1. Microsoft Research, Redmond, WA, USA

    Nikolaj Bjørner

  2. AP Ershov Institute of Informatics Systems, Novosibirsk, Russia

    Irina Virbitskaite

  3. School of Computer Science, University of Manchester, Manchester, UK

    Andrei Voronkov

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Kuchuganov, V., Kasimov, D., Kuchuganov, A. (2019). A Logical Approach to the Analysis of Aerospace Images. In: Bjørner, N., Virbitskaite, I., Voronkov, A. (eds) Perspectives of System Informatics. PSI 2019. Lecture Notes in Computer Science(), vol 11964. Springer, Cham. https://doi.org/10.1007/978-3-030-37487-7_13

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  • DOI: https://doi.org/10.1007/978-3-030-37487-7_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37486-0

  • Online ISBN: 978-3-030-37487-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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