Edge detection is a technique in image processing to identify the boundaries of an objects within the image. Edge detection is used in image segmentation and data extraction in image processing, computer vision.
For example, edges are used to detect specific objects of interest in an image.
How edge detection is identified?
It is identified by detecting discontinuities in brightness of an image. There are many algorithms available to detect the edges. Following are most common ones.
Sobel Operator: It is a gradient-based edge detector. It calcualtes the magnitude of the gradient at each pixel in the image. The gradient is a measure of the change in intensity in the image. Pixels with a high gradient magnitude are likely to be on edges.
Canny edge detector: It is also a gradient-based edge detector. It is considered to be one of the best edge detection algorithms available.
Prewitt Operator: Similar to the Sobel operator but uses different convolution kernels.
Original image
Image detection using Canny edge detector
Image blurness vs edge detection
Image blurriness and edge detection are related, but they are not the same thing. A blurred image will have fewer and less distinct edges than a sharp image. This is because the blurring process causes the pixels in the image to blend together, making it difficult to identify the boundaries between objects.
Following image detects the edges on a blurred image.
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