To detect vertical edges we first convolve with a Gaussian and then
differentiate the resultant image in the 
direction. But this is
the
same as convolving the image with the Derivative Of the Gaussian (DOG)
in the x-direction, that is
Then, one marks the peaks in the resultant image that are above a prescribed threshold as edges (the threshold is chosen so as to minimize the effects of noise). The effects of doing this on the image of 1 are shown in 4.
Figure 4: Showing the vertical edges of the original noiseless image
