Abstract
Neurophysiological evidence demonstrates that classical receptive field responses in the primary visual cortex can be modulated by the non-classical receptive field. Although models based on the non-classical receptive field have been proposed, which has not employed the two following characteristics: dynamic regulation of the receptive field under external stimuli and depth determination by binocular cells. We propose a model that includes processing of gray-scale images and depth images. Luminance of grayscale image response was preprocessed using weighted least squares filtering; luminance of grayscale image and disparity information of depth image responses were obtained by V1 neuron responses. The receptive field size of each pixel used to calculate the luminance and disparity response is determined by the depth information. Luminance and disparity information responses were combined based on the optimal orientation, and robust contour maps were developed. Experimental results show that the proposed contour detection model outperforms biologically inspired models.
Published Version
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