Chaotic phase synchronization and desynchronization in an oscillator network for object selection

Object selection refers to the mechanism of extracting objects of interest while ignoring other objects and background in a given visual scene. It is a fundamental issue for many computer vision and image analysis techniques and it is still a challenging task to artificial visual systems. Chaotic ph...

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Bibliographic Details
Published in:Neural networks 2009-07, Vol.22 (5), p.728-737
Main Authors: Breve, Fabricio A., Zhao, Liang, Quiles, Marcos G., Macau, Elbert E.N.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Attention
Chaotic phase synchronization
Computer Simulation
Exact sciences and technology
Humans
Image processing
Information, signal and communications theory
Neural Networks (Computer)
Object selection
Periodicity
Photic Stimulation
Shifting mechanism
Signal and communications theory
Signal processing
Signal representation. Spectral analysis
Signal, noise
Telecommunications and information theory
Time Factors
Visual Perception
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Summary:Object selection refers to the mechanism of extracting objects of interest while ignoring other objects and background in a given visual scene. It is a fundamental issue for many computer vision and image analysis techniques and it is still a challenging task to artificial visual systems. Chaotic phase synchronization takes place in cases involving almost identical dynamical systems and it means that the phase difference between the systems is kept bounded over the time, while their amplitudes remain chaotic and may be uncorrelated. Instead of complete synchronization, phase synchronization is believed to be a mechanism for neural integration in brain. In this paper, an object selection model is proposed. Oscillators in the network representing the salient object in a given scene are phase synchronized, while no phase synchronization occurs for background objects. In this way, the salient object can be extracted. In this model, a shift mechanism is also introduced to change attention from one object to another. Computer simulations show that the model produces some results similar to those observed in natural vision systems.
ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2009.06.027