Implementation and Analysis of Image Processing Techniques using FPGA

Abstract

Image processing is an essential technique in various applications, such as medical imaging, security, and robotics. FPGA-based implementation of image processing algorithms provides high-performance processing and real-time operation for large amounts of data. This thesis presents an implementation and analysis of image processing techniques using FPGA hardware. With the invention of various applications involving artificial intelligence (AI) and the Internet of Things (IoT), there has been an overwhelming development in the field of image processing. Starting from basic image processing techniques such as image filtering, edge detection, and image segmentation to face recognition and objection recognition the application ranges over a wide area of research. The development of complex algorithms is also possible to be implemented due to the advancement of modern computing hardware and tools. Furthermore, modern computing computed paper also presents a detailed experimental analysis of the implemented techniques based on their processing time, accuracy, power consumption, and resource utilization.

The thesis begins by providing an overview of different image processing techniques, including image filtering, edge detection, and image segmentation along with the literature review. It then presents the implementation of these techniques on FPGA, including the architecture design, algorithm implementation, and software-hardware co-design. A detailed experimental analysis of the implemented techniques is presented, based on their processing time, accuracy, power consumption, and resource utilization. The experimental setup involves using a Xilinx Zynq XC7Z020-1CLG484C FPGA board and a 640×480 grayscale input image. The results show that FPGA implementation of image processing techniques can significantly improve the performance and speed of image processing. This thesis concludes with valuable insights into the trade-offs between different image processing techniques in FPGA implementation and their suitability for various applications. The presented work is a significant contribution to the field of FPGA-based image processing and can be used as a reference for researchers and practitioners working on FPGA implementation of image processing techniques. Furthermore, the thesis discusses the advantages and limitations of FPGA-based image processing techniques, including their flexibility, high performance, and real-time processing capabilities. However, the implementation of FPGA-based image processing requires significant expertise in hardware design and programming, which can be a barrier to entry for many researchers and practitioners. In conclusion, this thesis presents an in-depth analysis of the implementation and analysis of image processing techniques using FPGA. The experimental analysis shows a significant improvement in the performance and speed of image processing techniques when implemented on FPGA. The insights provided by the thesis can guide researchers and practitioners in choosing the most appropriate image-processing techniques for their specific application. The presented work is a valuable contribution to the field of FPGA-based image processing, and it can help accelerate the development of high-performance and real-time image processing systems.