Contour tracing is a critical technique in image analysis and computer vision, with applications in medical imaging, big data analytics, machine learning, and robotics. We introduce a novel hardware accelerator based ...
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Contour tracing is a critical technique in image analysis and computer vision, with applications in medical imaging, big data analytics, machine learning, and robotics. We introduce a novel hardware accelerator based on the adapted and segmented (AnS) vertex following (VF) and run-data-based-following (RDBF) families of fast contour tracing algorithms implemented on the Zynq-7000 field-programmable gate array (FPGA) platform. Our algorithmic implementation utilizing a mesh-interconnected multiprocessor architecture is at least 55x faster than the existing implementations. With input-output overheads, it is up to 12.5x faster. Our hardware accelerator for contour tracing is benchmarked on mesh-interconnected hardware, all three families of contour tracing algorithms, and a random image from the Imagenet database. Our implementation is, thus, faster for FPGA, application-specific integrated circuit (ASIC), graphics processing unit (GPU), and supercomputer hardware in comparison to the central processing unit (CPU)-GPU collaborative approach and offers a better solution for those systems where the input-output overheads can be minimized, such as parallel processing arrays and mesh-connected sensor networks.
It has been shown previously that a bitlevel systolic adaptor can be developed from input/output equations. The design, however, was not fully pipelined and so did not make full use of the power inherent in systolic p...
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It has been shown previously that a bitlevel systolic adaptor can be developed from input/output equations. The design, however, was not fully pipelined and so did not make full use of the power inherent in systolic processors. The paper presents an improved architecture which exhibits much higher throughput. A simple modification to allow internal subtraction is also given and this is contrasted with externally complementing one of the inputs.
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