Performance analysis on visual attention using spiking and oscillatory neural model

Authors:
A. Diana Andrushia;R. Thangarajan;Greeshma Sebastian
Affiliations:
ECE Department, Karunya University, Coimbatore 641114, Tamil Nadu, India;CSE Department, Kongu Engineering College, Erode 638052, Tamil Nadu, India;ECE Department, Karunya University, Coimbatore 641114, Tamil Nadu, India
Venue:
International Journal of Computational Vision and Robotics
Year:
2013

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Abstract

Visual attention is a process of sustained concentration on a specific stimulus. This concentration can be increased by activating the nucleus basalis in the basal forebrain using the spiking neuron model. Input stimulus is converted into spikes. Neurons are transmitting information in the form of pulse. By using this information spiking neuron model for the basal forebrain is simulated. Bottom-up and top-down method is used in lateral geniculate nucleus LGN. The feedback connections are applied in the visual cortex for the enhancement of visual attention. To analyse the performance of spiking and oscillatory model segmentation and separation accuracy are obtained which shows the oscillatory model produce better accuracy for visual stimuli.