METHOD OF CONSTRUCTING HARDWARE ARCHITECTURE FOR COMPUTER VISION SYSTEM BASED ON FPGA

In this work, the methodology of hardware architecture development for computer vision systems based on programmable logic, in particular FPGA, is considered. In the work, the methods of developing architectures for computer vision are studied and the advantages of using FPGA compared to traditional general-purpose processors are established. The paper also considers the main aspects of hardware design on FPGA, in particular, the selection of a suitable development tool, logic design, synthesis, and validation of the developed hardware. The capabilities of FPGAs in providing high performance and efficiency of computer vision systems have been investigated, which makes them attractive and popular for use in visual systems. We discover that FPGA technology offers a high degree of flexibility and configurability, allowing for the creation of custom hardware architectures that can be tailored to specific computer vision applications. In addition, to studying the benefits of using FPGA technology for computer vision, we also consider the main aspects of hardware design on FPGA, including the selection of a suitable development tool, logic design, synthesis, and validation of the developed hardware. By carefully considering these aspects, we can ensure that the hardware architecture we develop is both efficient and effective. Our research shows that the capabilities of FPGAs in providing high performance and efficiency of computer vision systems are truly remarkable. This makes them an attractive choice for use in visual systems, particularly in scenarios where high speed and accuracy are critical. Overall, our work serves to shed light on the many benefits of FPGA technology for computer vision and lays the foundation for further research and development in this exciting field.