OBJECTS RECOGNITION ON DYNAMIC BACKGROUND USING TWO-DIMENSIONAL PREDICTION MODEL WITH QUADRATIC NONLINEARITY

Authors

  • Roman Kvietnyy Vinnytsia National Technical University
  • Olga Bunyak Vinnytsia National Technical University

Abstract

Method of objects recognition on dynamic background is researched in given work. Stochastic, linear and nonlinear prediction models are used for modelling of dynamic background as a signal that is changed in time and space. The best quality of object definition is received with help of simplified nonlinear model as a sum of linear and quadratic signal components. Influences of model order, supporting area size and threshold value on the signal object selection are researched.

Author Biographies

Roman Kvietnyy, Vinnytsia National Technical University

Head of the Department

Olga Bunyak, Vinnytsia National Technical University

Master student of the Department

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How to Cite

[1]
R. Kvietnyy and O. Bunyak, “OBJECTS RECOGNITION ON DYNAMIC BACKGROUND USING TWO-DIMENSIONAL PREDICTION MODEL WITH QUADRATIC NONLINEARITY”, Works of VNTU, no. 1, Dec. 2011.

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Section

Automatics and Information Measuring Facilities

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