FPGA Implementation of the Lane Detection and Tracking Algorithm

The application of the Image Processing to Autonomous Drive has drawn a significant attention in the literature and research. However the demanding nature of the image processing algorithms conveys a considerable burden to any conventional real-time implementation. Meanwhile the emergence of FPGAs has brought numerous facilities toward fast prototyping and implementation of ASICs so that an image processing algorithm can be designed, tested and synthesized in a relatively short period of time in comparison to traditional approaches. This thesis investigates the best combination of required algorithms to reach an optimum solution to the problem of lane detection and tracking while is aiming to fit the design to a minimal system. The proposed structure realizes three algorithms namely Steerable Filter, Hough Transform and Kalman Filter. For each module the theoretical background is investigated and a detailed description of the realization is given followed by an analysis of both achievements and shortages of the design. Acknowledgments Many thanks to my supervisor Professor Dr Thomas Braunl for his invaluable support and guidance throughout the course of this project. I would like to gratefully express my thanks and love to my family Vida, Javad and Hormoz who have always been supporting me unconditionally.