detector was derived from similar mathematical criteria as the Canny edge detector, although starting from a discrete viewpoint and then leading to a set of recursive filters for image smoothing instead of exponential filters or Gaussian filters. The differential edge detector described below can be seen as a reformulation of Canny's method from the viewpoint of differential invariants computed from a scale space representation leading to a number of advantages in terms of both theoretical analysis and sub-pixel implementation. In that aspect, Log Gabor filter have been shown to be a good choice to extract boundaries in natural scenes. Other first-order methods Different gradient operators can be applied to estimate image gradients from the input image or a smoothed version of it. The simplest approach is to use central differences: corresponding to the application of the following filter masks to the image data: The well-known and earlier Sobel operator is based on the following filters: Given such estimates of first-order image derivatives, the gradient magnitude is then computed as: while the gradient orientation can be estimated as Other first-order difference operators for estimating image gradient have been proposed in the Prewitt operator, Roberts cross, Kayyali operator and Frei–Chen operator. It is possible to extend filters dimension to avoid the issue of recognizing edge in low SNR image. The cost of this operation is loss in terms of resolution. Examples are Extended Prewitt 7×7. Thresholding and linking Once we have computed a measure of edge strength (typically the gradient magnitude), the next stage is to apply a threshold, to decide whether edges are present or not at an image point. The lower the threshold, the more edges will be detected, and the result will be increasingly susceptible to noise and detecting edges of irrelevant features in the image. Conversely a high threshold may miss subtle edges, or result in fragmented edges. If the edge is applied to just the gradient magnitude image, the resulting edges will in general be thick and some type of edge thinning post-processing is necessary. For edges detected with non-maximum suppression however, the edge curves are thin by definition and the edge pixels can be linked into edge polygon by an edge linking (edge tracking) procedure. On a discrete grid, the non-maximum suppression stage can be implemented by estimating the gradient direction using first-order derivatives, then rounding off the gradient direction to multiples of 45 degrees, and