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Physical computing is a technology utilizing the nature of electronic devicesand circuit topology to cope with computing tasks. In this paper, we propose anactive circuit network to implement multi-scale Gaussian filter, which is alsocalled Gaussian Pyramid in image preprocessing. Various kinds of methods havebeen tried to accelerate the key stage in image feature extracting algorithmthese years. Compared with existing technologies, GPU parallel computing andFPGA accelerating technology, physical computing has great advantage onprocessing speed as well as power consumption. We have verified that processingtime to implement the Gaussian pyramid of the SIFT algorithm stands onnanosecond level through the physical computing technology, while otherexisting methods all need at least hundreds of millisecond. With an estimate onthe stray capacitance of the circuit, the power consumption is around 670pJ tofilter a 256x256 image. To the best of our knowledge, this is the most fastprocessing technology to accelerate the SIFT algorithm, and it is also a ratherenergy-efficient method, thanks to the proposed physical computing technology.

Physical Computing With No Clock to Implement the Gaussian Pyramid of SIFT Algorithm