The detection and tracing of edges of varying diffusion is a problem of importance in image analysis. In particular, it is of interest for the segmentation of meteorological and physiological pictures where the boundaries of objects are possibly not well defined or are obscured to a varying extent by noise. We present an edge detection and line fitting procedure which ascribes a direction, a measure of gradient, and quality of fit to the edge within a square segment of a controlled size or ``scope.'' To detect and fit edges to diffuse objects the scope is adaptively altered based on the confidence of fit to permit tracing of the object's boundary. We discuss predictor-corrector procedures for performing this edge tracing where predicted and calculated lines and confidences are used to generate a better fitting line. The performance of the procedures is demonstrated using both synthetic and satellite meteorological images.