In this paper, a new wave computing algorithm for edge detection in real images is introduced. This algorithm is suitable for real time applications due to the parallel processing capabilities of CNN. The new algorithm is based on the wave computing concept, using diffusion for noise reduction and weak edge elimination and trigger wave to emphasize the strong edges in the image. The proposed algorithm finds edge maps in eight directions and these maps are summed to produce final edge map. The performance of our proposed algorithm is evaluated and compared with different diffusion models using the Berkeley dataset BSDS300 with its benchmark. Experimental results demonstrate superiority of our proposed for real images.
