Edge Detection. Edge Detection. Edges characterize boundaries of objects in image A fundamental problem in image processing Edges are areas with strong intensity contrasts A jump in intensity from one pixel to the next Edge detected image Reduces significantly the amount of data,
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Our goal is to extract a “line drawing” representation from an image
the signs of the derivatives would be reversed for an edge that transitions from light to darkFirst and Second Derivatives
(x,y) = tan-1(Gy/Gx)
Sobel masks have slightly superior noise-suppression characteristics which is an important issue when dealing with derivatives.
Same sequence as previous figure, but with original image smoothed with a 5 x 5 averaging filter
surrounded by an adjacent negative region (a function of distance)
zero outer regionMexican Hat
the coefficient must be sum to zero
To overcome the effect of noise, smoothing operation is performed before edge detection
Or generate the combined mask of LOG
Smoothing by Gaussian convolution
Differential operators along x and y axis
finds peaks in the image gradient
Hysteresis thresholding locates edge strings