Shape description by time series

Shape description by time series

Time series modeling techniques are adapted to represent or describe two-dimensional closed contours. Both linear and nonlinear models are fitted. It is found that to detect small changes in shape nonlinear modeling is necessary, even though linear models may be sufficient to differentiate between s...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 1989-09, Vol.11 (9), p.977-984
Hauptverfasser: Kartikeyan, B., Sarkar, A.
Format: Artikel
Sprache:eng
Schlagworte:
Aircraft
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Digital images
Exact sciences and technology
Feature extraction
Image analysis
Image recognition
Mathematics
Pattern recognition. Digital image processing. Computational geometry
Shape
Stochastic processes
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Beschreibung
Zusammenfassung:Time series modeling techniques are adapted to represent or describe two-dimensional closed contours. Both linear and nonlinear models are fitted. It is found that to detect small changes in shape nonlinear modeling is necessary, even though linear models may be sufficient to differentiate between shapes which differ widely. A nonlinear model called the noncausal quadratic Volterra model is developed for the purpose. Implementation is illustrated with shapes of aircraft.< >
ISSN:0162-8828
1939-3539
DOI:10.1109/34.35501