Object Recognition on a Chip: A Complete SURF-Based System on a Single FPGA

Abstract

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 lightweightmatching 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.