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Daniil, DoG is one of the methods to detect edges in image without calculating gradients. Original image smoothed twice with Gaussian kernels with different sigmas. DoG is the difference of those two images. See wikipedia for details.

DS, Gaussian kernel is blurs the image equally in all directions (in theory at least). What do you mean by passing same values to x and y?