Contour Detection by a Dark-Adaptation Model

Abstract

The color contour detection model used for simulating the cone photoreceptor cell- lateral geniculate nucleus (LGN) – primary visual cortex (V1) visual pathway has achieved reliable results. In contrast, the rod photoreceptor cells employ a dark adaptive mechanism, which plays a key role in contour extraction in poorly lit environments. We employ this mechanism to propose a bionic model for contour detection. The proposed model divides the dark adaptation process into several stages and extracts the image information at each stage for subsequent integration. For evaluation, we applied the proposed dark adaptation model as the front-end processing method of the gray and color contour detection model, and performed experimental verification on the RuG, BSDS300/500, and NYUD databases. In comparison with a similar state-of-the-art model, the detection performance of the proposed model has several advantages; in particular, it extracts contour information more effectively in interior scenes lit with dim colors.