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title: Lecture: Edge Detection
categories: lecture
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# Differentiation - The Canny edge detector
+ $\nabla I = [ I_x, I_y ]$ is the gradient vector.
+ It has length and direction in each pixel in the image.
+ Length $||\nabla I(x,y)||^2= \nabla I^T\nabla I$
+ Select points which satisfy two criteria
+ Local optimum *along the direction of the gradient*
+ Larger than a chosen threshold $\tau$.
+ Sometimes we use a soft and a hard threshold, where
points between the two thresholds are selected if they
are adjacent to other selected points.
+ We can calculate $\nabla I$ with either Sobel or the derivative
of a Gaussian.
# Connected Components
# Line Fitting
# Hough