An effusion–evaporation model for image edge detection

A novel quasi-physical edge detection model is presented. The model, referred to as the effusion–evaporation model (EEM), is inspired by the natural phenomenon that the water effusing from the ground evaporates in the sunshine and leaves a wire like water stain on the ground surface, which reflects the physiognomy of the terrain. Based on the simulation of water effusing and evaporating, an EEM regards the complement of gradient magnitude image as a three-dimensional terrain, and the concave regions, which contain the residual water in the evolution final state, are used to determine the edges. Subjective and objective comparisons are performed on the proposed algorithm and two conventional edge detectors, namely Canny and LoG. The comparison results show that the proposed method outperforms Canny and LoG detectors for the real images and the standard test images with Gaussian noise.

Research highlights
► This paper presents a novel quasi-physical edge detection model, referred to as the effusion–evaporation model (EEM).
► Based on the simulation of water effusing and evaporating, an EEM regards the complement of gradient magnitude image as a three-dimensional terrain, and the concave regions, which contain the residual water in the evolution final state that are used to determine the edges.
► The proposed method is robust for Gaussian noisy images and outperforms the Canny and LoG detectors in the edge accurate localization.