Moving-edge detection via heat flow analogy

In this paper, a new and automatic moving-edge detection algorithm is proposed, based on using the heat flow analogy. This algorithm starts with anisotropic heat diffusion in the spatial domain, to remove noise and sharpen region boundaries for the purpose of obtaining high quality edge data. Then, isotropic and linear heat diffusion is applied in the temporal domain to calculate the total amount of heat flow. The moving-edges are represented as the total amount of heat flow out from the reference frame. The overall process is completed by non-maxima suppression and hysteresis thresholding to obtain binary moving-edges. Evaluation, on a variety of data, indicates that this approach can handle noise in the temporal domain because of the averaging inherent of isotropic heat flow. Results also show that this technique can detect moving-edges in image sequences, without background image subtraction.

Research highlights
► A new and automatic moving-edge detection algorithm is proposed, based on using the heat flow analogy.
► Evaluation indicates that our approach can handle noise in the temporal domain because of the averaging inherent of isotropic heat flow. The proposed moving-edge detection operator performs better than 2-D Canny and 2-D Sobel based operators.
► Results show that this technique can detect moving-edges in image sequences, without background image subtraction. The proposed technique can be applied to indoor and outdoor sequences for moving-edge detection. Experiments also show that the proposed algorithm can detect moving-edges, which belong to the different moving objects in the scene.