The Canny edge is a popular edge-detection algorithm. It can detect a wide range of edges. The Canny edge detection algorithm was developed by John F. Canny in 1986. The Canny edge is widely used in the field of computer vision, as it has a wide range of applications.
The process of Canny edge detection has the following criteria:
- The edges of images should be detected with high accuracy.
- Only one marks should be created for one image; there should not be any duplicate marks.
- The detected edges should be correctly localized on the image.
- Granular edges should also be detected.
The Canny edge detection algorithm is applied using the following steps:
- In the first step, a Gaussian filter is applied to smooth the image. Smoothing the image removes the noise.
- Next, we find the intensity gradient of the image.
- Then, we apply nonmaximum suppression to remove any fake edge detection response.
- Next, we apply a double-threshold on the image to determine the accuracy...
