The Canny edge detection algorithm can be broken down into 5 steps:

## How do you implement Canny edge detection?

The Canny edge detection algorithm can be broken down into 5 steps:

1. Step 1: Smooth the image using a Gaussian filter to remove high frequency noise.
2. Step 2: Compute the gradient intensity representations of the image.
3. Step 3: Apply non-maximum suppression to remove “false” responses to to edge detection.

## What is canny edge detection in image processing?

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. (

How does the Canny edge detector work?

The Canny filter is a multi-stage edge detector. It uses a filter based on the derivative of a Gaussian in order to compute the intensity of the gradients. The Gaussian reduces the effect of noise present in the image.

### What are the three stages of the Canny edge detector?

The goals of the Canny Operator were stated explicitly. Good Detection: the ability to locate and mark all real edges. Good Localisation: minimal distance between the detected edge and real edge. Clear Response: only one response per edge.

### Why Canny edge detection is better?

The canny edge detection first removes noise from image by smoothening. It then finds the image gradient to highlight regions with high spatial derivatives. The algorithm then tracks along these regions and suppresses any pixel that is not at the maximum (non maximum suppression).

What is canny edge detection Opencv?

Canny Edge Detection is used to detect the edges in an image. It accepts a gray scale image as input and it uses a multistage algorithm. You can perform this operation on an image using the Canny() method of the imgproc class, following is the syntax of this method.

## What is Canny in open CV?

Canny() Function in OpenCV is used to detect the edges in an image.

Is Canny edge detector linear?

The Canny edge detector is a linear filter because it uses the Gaussian filter to blur the image and then uses the linear filter to compute the gradient.

### What is the effect of sigma on the canny edge detection?

sigma plays the role of a scale parameter for the edges: large values of sigma produce coarser scale edges and small values of sigma produce finer scale edges. Larger values of sigma also result in greater noise suppression.

### Is Canny better than Sobel?

The Sobel edge detector and Prewitt edge detector are able to detect edges but the edges detected are very less as compare to Canny edge detector. After all these results and comparative images, it is found that the performance of Canny edge detector is better than Sobel and Prewitt edge detector.

Which is better Canny and Sobel?

The main advantages of the Sobel operator are that it is simple and more time-efficient. However, the edges are rough. On the other hand, the Canny technique produces smoother edges due to the implementation of Non-maxima suppression and thresholding.