Moving images time gradient implementation using RAM-based FPGA

Time gradient can be used to extract information from motion. It has been already done, but higher performances are reached if it's computed on real time (at video rate). We propose an architecture to evaluate it from consecutive images in a video signal. Behind a delaying structure, a circuit operates over the neighbourhood of pixels around each one: not only the adjacent pixels in space but also in time (in several previous images), Gradient can be extracted from all of them by convolution, and other non-linear algorithms can also be applied. Known 3x3 masks to operate over static images are generalized by 3D masks (3x3x3) to operate over dynamic images. The circuit is based on Field Programmable Gate Array (FPGA) devices, them, a set of specific purpose hardware designs can be loaded on RAM cells in FPGA, so it's fast as hardware and versatile as software, and different approaches of gradient can be implemented from host computer to programmable logic in FPGA.