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Compound Objects Comparators in Application to Similarity Detection and Object Recognition

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Transactions on Rough Sets XXI

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 10810))

Abstract

This article presents similarity based reasoning approach for recognition of compound objects. It contains mathematical foundations for comparators theory as well as comparators network theory. It shows also three different practical applications in field of image recognition, text recognition and risk recognition.

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Notes

  1. 1.

    Knowledge discovery in databases.

  2. 2.

    pl.wikipedia.org/wiki/RFID.

  3. 3.

    \( [0,1]^{ref}\) this is a designation of the vector space \(\varvec{v}\) with the length |ref|, where each i’th coordinate \(v[i]\in [0,1]\) refers to the element \(y_{i}\in ref\), \(ref=\{y_1,\ldots ,y_{|ref|}\}\).

  4. 4.

    National Register of Territorial Divisions.

  5. 5.

    https://pl.wikipedia.org/wiki/RGB.

  6. 6.

    https://en.wikipedia.org/wiki/Flood_fill.

  7. 7.

    The next extreme point is chosen clockwise, basing on the 8-point neighborhood, remembering the recently visited points in order to backtrack, if necessary.

  8. 8.

    https://en.wikipedia.org/wiki/Levenshtein_distance.

  9. 9.

    http://www.icra-project.org.

  10. 10.

    Reporting and evidence system used by the State Fire Service.

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  1. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Łukasz Sosnowski

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  1. University of Manitoba, Winnipeg, MB, Canada

    James F. Peters

  2. University of Warsaw, Warsaw, Poland

    Andrzej Skowron

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Sosnowski, Ł. (2019). Compound Objects Comparators in Application to Similarity Detection and Object Recognition. In: Peters, J., Skowron, A. (eds) Transactions on Rough Sets XXI. Lecture Notes in Computer Science(), vol 10810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-58768-3_6

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