Search results
Results from the WOW.Com Content Network
The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images. It was developed by John F. Canny in 1986. Canny also produced a computational theory of edge detection explaining why the technique works.
Deriche edge detector is an edge detection operator developed by Rachid Deriche in 1987. It is a multistep algorithm used to obtain an optimal result of edge detection in a discrete two-dimensional image. This algorithm is based on John F. Canny's work related to the edge detection (Canny's edge detector) and his criteria for optimal edge ...
The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal discontinuities over time is known as change detection. Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature ...
Today, there are much better edge detection methods, such as the Canny edge detector based on the search for local directional maxima in the gradient magnitude, or the differential approach based on the search for zero crossings of the differential expression that corresponds to the second-order derivative in the gradient direction (both of ...
Uses edge detection techniques, such as the Canny edge detection, to find edges. Changes in lighting and color usually don't have much effect on image edges; Strategy: Detect edges in template and image; Compare edges images to find the template; Must consider range of possible template positions; Measurements:
A color picture of an engine The Sobel operator applied to that image. The Sobel operator, sometimes called the Sobel–Feldman operator or Sobel filter, is used in image processing and computer vision, particularly within edge detection algorithms where it creates an image emphasising edges.
The result therefore shows how "abruptly" or "smoothly" the image changes at that point, and therefore how likely it is that part of the image represents an edge, as well as how that edge is likely to be oriented. In practice, the magnitude (likelihood of an edge) calculation is more reliable and easier to interpret than the direction calculation.
Canny has published several books, papers and articles. A selection: 1986. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, 1986, pp. 679–698. 1988. The Complexity of Robot Motion Planning. The ACM Distinguished Dissertation Series, Cambridge, MA: The MIT Press, 1988. 1993.