| Abstract: |  The thesis presents a complete hardware and software solution of a FPGA-based computer vision embedded module capable of carrying out SURF image features extraction algorithm. The module is based on Virtex-5 FXT FPGA which features, aside from powerful configurable logic, embedded PowerPC-440 processor. A set of custom FPGA image processing IP cores is described along with its drivers for Linux OS which controls the module.
These IP cores cover the detection part of the SURF algorithm, offloading algorithm most computationally expensive processes into FPGA logic. The module performance and power consumption is evaluated and the results from module practical application for a mobile robot SLAM are presented to document that the module achieves comparable accuracy to other SURF implementations, while consuming significantly less power and space.
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