The Difference-of-Low-Pass (DOLP) Transform uses a hierarchy of bandpass filters to perform size discrimination and pattern matching of objects and features in a visual field. Like the Discrete Fourier Transform (DFT), it "sorts" entities according to their size or spatial frequencies; but unlike the DFT, it also retains positional information.This positional information is essential for the very common industrial web inspection problem in which a "flaw map" must be produced - mere flaw detection (as provided by the DFT) is not enough. The DOLP Transform is usually implemented using finite-impulse-response difference-of-Gaussian (DOG) filters of progressively increasing kernel size. Various potential industrial applications have been described and demonstrated, but implementations have been hampered by the heavy computational burden involved in the generation of the Transform. This paper describes a fast implementation of Crowley's resampled DOLP Transform using commercially-available board-level hardware. With a moderate investment in hardware modules, a nine-band DOLP Transform can be computed for a 485 by 512 image in about one second. Additional hardware modules could be added to bring the speed up to 30 complete 9-band Transforms per second, if desired. Additional bands beyond the first nine, while seldom needed, require very little additional time, because the image has been repeatedly resampled down to a small size.