Edge detection is the first step for some boundary extraction and boundary representation algorithms. In this paper, a fuzzy switch approach is proposed. Different existing edge filters, such as Sobel filter, Prewitt filter, Roberts filter, Isotropic filter and Canny filter, are viewed as different expert systems. In order to capture the knowledge from these expert systems, a fuzzifier is employed, which normalizes the output of each edge filter to a matrix with the values of its elements being in between zero and one. By comparing the corresponding elements in these matrices, those with the highest values are with the highest fuzzy membership values of being at an edge point. A fuzzy engine can then be designed to select the highest fuzzy membership values. Then, a defuzzifier maps the selected membership value to a crisp point, which is either zero or one. Simulations were carried out using the Sobel filter, Prewitt filter, Roberts filter, Isotropic filter and Canny filter as the edge filters. It can be concluded from the simulations that the proposed algorithm captures the advantages of the expert filters.