Geometric Computer Vision: Difference between revisions

Geometric Computer Vision (view source)

843 bytes added , 2 February 2021

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 ;Laplacian of Gaussian
 * Edges are zero crossings of the Laplacian of Gaussian convolved with the signal.
+Effect of <math>\sigma</math> Gaussian kernel size:
+* Large sigma detects large scale edges.
+* Small sigma detects fine features.
+;Scale Space
+* With larger sigma, the first derivative peaks (i.e. zero crossings) can move.
+* Close-by peaks can also merge as the scale increases.
+* An edge will never split.
+===Subtraction===
+* Create a smoothed image by convolving with a Gaussian
+* Subtract the smoothed image from the original image.
+===Finding lines in an image===
+Option 1: Search for line everywhere.
+Option 2: Use Hough transform voting.
+===Hough Transform===
+Duality between lines in image space and points in Hough space.
+Equation for a line in <math>d = x \cos \theta + y \sin \theta</math>.
+<pre>
+for all pixels (x,y) on an edge:
+  for all d, theta:
+    if d = x*cos(theta) + y*sin(theta):
+       H(d, theta) += 1
+</pre>