An edge detection is one of the most important tasks in image processing. Image segmentation, registration and identification are based on edge detection. In the literature, there is some techniques developed to achive this task such as Sobel, Prewitt, Laplacian and Laplacian of Gaussian. In this paper, a novel knowledge-based approach which have been used to realize control techniques for past years is proposed for edge detection. Some of the classical techniques are used with certain parameters such as threshold and sigma to implement edge detection process. The another restricts about classial approach, results generally have fixed edge thickness. The rule-based approach offers most advantages such as giving permission to adapt some parameters easily. The edges thickness can be changed easily by adding new rules or changing output parameters. That is to say rule-based approach has flexible structure which can be adapted any time or any where easily and new fuzzy approach produces nice result as well as classical techniques at least.