In order to improve the preservation of edge details and reduce false edges caused by noise in edge detection algorithm, an edge detection scheme based on the theory of Intelligence and direction αmean was designed. Firstly, based on the theory of ChiChi, the image is transformed into intelligence image, and the intelligence image was represented by three authenticity T, uncertainty I and false F members, which improves the expression ability of uncertain information such as noise. Then, in order to remove the noise effectively and keep the edge, the direction mask of the pixel was calculated, and a directionmean operator was defined by the direction average function. Then anisotropic filtering was performed on the image using the generated directionmean algorithm. Finally, an iteration equation was defined to determine whether a pixel was an edge pixel by judging the threshold of gradient. Experiments show that the proposed method can detect edges effectively and accurately compared with current popular algorithms. It can eliminate the influence of noise at different noise levels, reduce the generation of false edges and discontinuous edges, and provide a good basis for future industrial automation and intellectualization.