Abstract
A systematic approach to geometrically invariant pattern description is proposed. It is based on the definition of transformation invariants. The generalized auto-correlation function is introduced as a signal representation from which such invariant descriptors can be derived. Descriptors remaining invariant under all similarity transformations are briefly discussed.
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© 1987 Springer-Verlag Berlin Heidelberg
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Glünder, H. (1987). Invariant Description of Pictorial Patterns via Generalized Auto-Correlation Functions. In: Meyer-Ebrecht, D. (eds) ASST ’87 6. Aachener Symposium für Signaltheorie. Informatik-Fachberichte, vol 153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-73015-3_15
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DOI: https://doi.org/10.1007/978-3-642-73015-3_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-18401-0
Online ISBN: 978-3-642-73015-3
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