A visual cortex domain model for surface perception of illusory contour figures

This study alms at proposing a novel method which can perceive surfaces of illusory contour figures by using a neural network model based on the mechanism of feature extraction found in a visual carter domain. A common factor in all such illusory contour figures, such as the Kanizsa triangle is the perception of a surface(contour) occluding part of a background, i.e. illusory contours are always accompanied by illusory surfaces. In this paper, we propose a neural network model that predicts the shape of illusory surfaces based on features of the visual cortex domain. This model employs an important two-stage process of the Induced Stimuli Extraction System(ISES) and Illusory Surfaces Perception System(ISPS). The former system extracts the induced stimuli for the perception of illusory surfaces, and the latter forms the illusory surfaces from the induced stimuli. The proposed model is demonstrated on a variety of Kanizsa-type illusory contorts displays. The results of the experiment showed that the proposed model was successful not only in extracting the induced stimuli for the perception of illusory contours, but also in perceiving the illusory surface from the induced stimuli.