Project
FPGA Edge Detection
This project involved designing and implementing an edge detection system using FPGA technology through digital signal processing (DSP). Using the HDL Verilog hardware description language, I programmed the system to detect edges in images or input signals with high efficiency in real-time.
The project integrated several technologies, starting with the implementation of the edge detection algorithm in Verilog for the FPGA, leveraging its parallel processing capabilities to analyze signals quickly and efficiently. Additionally, MATLAB was used for simulation and validation of the algorithm before it was implemented on the FPGA, ensuring its correct operation and optimization.
The final part of the project involved integrating with a Raspberry Pi, which acted as a controller for the FPGA. The system received input signals via the Raspberry Pi and processed the edge detection results, allowing for more dynamic interaction with the hardware and providing an accessible means for visualizing and analyzing processed data.
This project deepened my understanding of advanced signal processing concepts and embedded system design, as well as giving me a thorough understanding of using FPGAs for high-speed applications. It also allowed me to work with tools like Verilog and MATLAB, and become familiar with using Raspberry Pi as a control platform for embedded systems, making it a rewarding experience for my engineering development.
#hdl
#fpga
#matlab
