VC: Edge Detection
The nature of the image is actually edges. Edge detection extracts salient features of the image by subtracting complex intensities in the image. Edges are caused by a variety of factors. There are four examples of edges, surface normal discontinuity, depth discontinuity(surface is not ended but we cannot see it in the image), surface color discontinuity, and illumination discontinuity(shadow is ended). From now on, I am going to explain how we detect those edges in the image.
What is the edge?
I explained to you four types of edges. Is there any commonality among those edges?
It is a place of rapid change in the image intensity function. We can detect the edges by differentiation. If we find the maximum or minimum of the first derivative, then we can find where the edges start or end.
How can we differentiate a digital image?
The digital image is discretized, it means the intensity is not continuous. Therefore, we cannot use normal differentiation. There are two options. Option 1 is to reconstruct a continuous image, then compute the derivative. If our digital image is fulfilled the Nyquist Theorem, we…
