A parametric method for edge detection based on recursive mean-separate image decomposition

Edge detection has played an important role in the field of computer vision. A parametric edge detection method based on recursive mean-separate image decomposition is introduced. A method for automatic parameter selection and two methods for thresholding are also suggested. Experimental results show that the proposed method outperforms many popular edge detection methods, including Sobel, Prewitt, Frei-Chen, and Canny both visually and by quantitative edge map evaluation. Proper parameter selection can also provide segmentation of materials such as potential threat objects in X-ray luggage scan images.