International Journal of Reconfigurable Computing - Special issue on Selected Papers from the 2011 International Conference on Reconfigurable Computing and FPGAs (ReConFig 2011)
FPGA-based module for SURF extraction
Machine Vision and Applications
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This paper describes a system for robust optical object recognition based on sophisticated point features which is completely implemented in a medium-size FPGA. All components needed to process image data are integrated in a System-on-Chip, including a special IP core which accelerates the feature detection step of the Speeded-up Robust Features (SURF) algorithm. The task of object recognition is solved by a lightweight matching algorithm. The system was evaluated with a set of 60 scene images. All 7 test objects were recognized at a sensitivity of 93% without any false positives at all. The minimum total execution time for one frame was 191ms, and the average time was 481ms.