Computer Vision Foundations · free preview
Edges and the Image Gradient
Treat the image as a function of position, measure its rate of change with the gradient, and turn sharp changes into edge pixels.
1. The image is a function of position
The image is a function of position
2. The gradient measures local change
The gradient measures local change
3. Finite differences on a pixel grid
Finite differences on a pixel grid
4. Edge strength, orientation and the normal
Edge strength, orientation and the normal
5. Which way the gradient points at an edge
A photograph shows a dark block against a bright white ground, and one image column crosses the block's left boundary, where intensity rises steeply from the dark block to the bright ground as you move right. At a pixel sitting on this boundary, which direction does the image gradient point?
6. Thresholding edge strength
Four pixels in an image have gradients , , and . Using edge strength with threshold , which pixels are marked as edges?
7. Computing a finite difference
A grayscale image satisfies the finite-difference approximation . At one pixel the intensity is and its left neighbor has . Compute the estimated horizontal derivative at this pixel and write the number.
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