Extraction of salient contours from cluttered scenes

The responses of neurons in the primary visual cortex (V1) to stimulus inside the receptive field (RF) can be markedly modulated by stimuli outside the classical receptive field. The modulation, relying on contextual configurations, yields excitatory and inhibitory activities. The V1 neurons compose a functional network by lateral interactions and accomplish specific visual tasks in a dynamic and flexible fashion. Well-organized structures and conspicuous image locations are more salient and thus can pop out perceptually from the background. The excitatory and inhibitory activities give different visual physiological interpretations to the two kinds of saliencies. A model of contour extraction, inspired by visual cortical mechanisms of perceptual grouping, is presented. We unify the dual processes of spatial facilitation and surround inhibition to extract salient contours from complex scenes, and in this way coherent spatial configurations and region boundaries could stand out from their surround. The proposed method can selectively retain object contours, and meanwhile can dramatically reduce non-meaningful elements resulting from a texture background. This work gives a clear understanding for the roles of the inhibition and facilitation in grouping, and provides a biologically motivated computational strategy for contour extraction in computer vision.