SURF algorithm in FPGA: A novel architecture for high demanding industrial applications

Today many industrial applications require object recognition and tracking capabilities. Feature-based algorithms are well-suited for such operations and, among all, Speeded Up Robust Features (SURF) algorithm has been proved to achieve optimal results. However, when high-precision and real time requirements come together, a dedicated hardware is necessary to meet them. In this paper we present a novel architecture for implementing SURF algorithm in FPGA, along with experimental results for different industrial applications.

[1]  Ioannis Papaefstathiou,et al.  Fast and Efficient FPGA-Based Feature Detection Employing the SURF Algorithm , 2010, 2010 18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines.

[2]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[3]  Gundolf Kiefer,et al.  Flex-SURF: A Flexible Architecture for FPGA-Based Robust Feature Extraction for Optical Tracking Systems , 2010, 2010 International Conference on Reconfigurable Computing and FPGAs.

[4]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[5]  Cordelia Schmid,et al.  A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.

[6]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .