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As the detection forms a key component of real-time localisation systems, a three-fold innovation is presented, consisting of an optimised procedure for CPUs, a GPU shader program, and a functionally equivalent FPGA streaming architecture. For the proposed CPU and GPU solutions, the mean processing time per pixel of input camera frames was accelerated by two to three orders of magnitude compared to the unoptimised state-of-the-art approach. For the localisation task, the proposed FPGA architecture offered the most significant overall acceleration by minimising the total delay from camera exposure to detection results. Additionally, the proposed solutions were evaluated on various 32-bit and 64-bit embedded platforms to demonstrate their efficiency, as well as their feasibility for applications using low-end UAVs and MAVs. 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