Abstract
Corner detection plays an essential role in many computer vision applications, e.g., object recognition, motion analysis and stereo matching. Several hardware implementations of corner detection algorithms have been previously reported to meet the real-time requirements of such applications. However, most of the reported implementations adopt similar computational flow which limit their potential for further area-time optimizations. In this paper, we propose a novel hardware design for the FAST corner detector, which unrolls the data-path to perform partial evaluation of multiple corners in a pipelined manner. We then apply logic folding that maximizes the design regularity of the unrolled data-path for resource sharing of the combinational operations. We show that the proposed design on FPGA leads to 20% reduction in critical path delay and about 39% reduction in area-delay product compared to a previously reported architecture. The real-time capability of the proposed FAST corner detectors is demonstrated on the TERASIC DE2i-150 FPGA development kit.
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Notes
Realizing the proposed method using a \(1 \times\) clock frequency of 125 MHz may not be possible on some of the existing FPGA systems.
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Lam, SK., Lim, T.C., Wu, M. et al. Data-path unrolling with logic folding for area-time-efficient FPGA-based FAST corner detector. J Real-Time Image Proc 16, 2147–2158 (2019). https://doi.org/10.1007/s11554-017-0725-0
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DOI: https://doi.org/10.1007/s11554-017-0725-0