Design Of High-resolution Image Acquisition And Transmission System Based On ZYNQ

With the continuous development of machine vision technology in the industrial field,traditional machine vision systems are unable to meet the requirements in terms of processing efficiency and speed.The complexity of the environment will increase the difficulty of image acquisition,whether in the military field of aerospace or in daily applications.People’s pursuit of image quality and transmission speed is increasing,and the requirements for image processing efficiency are also becoming increasingly stringent.How to design an image acquisition and transmission system with rich functions,high imaging quality,and fast transmission speed is the key to this study.The ZYNQ-7000 series devices released by Xilinx Company integrate the Xilinx 7 series FPGA and dual core Cortex-A9 processor together.This not only improves the overall performance of the system,but also enhances the data processing and communication capabilities of the embedded system.The embedded system based on the ZYNQ platform in this article adopts software hardware collaborative design,mainly centered on ARM dual core architecture processors,and ported the Linux operating system as the software platform.At the same time,FPGA is used for data transmission and processing to achieve system acceleration.In the hardware design section,an IP core for image acquisition,processing,and transmission was implemented using FPGA.The image sensor uses Sony’s IMX183,with a maximum resolution of 20 million pixels.The designed image acquisition IP is suitable for various modes of the IMX183 sensor.The image processing IP core integrates Sobel sharpening,Laplace sharpening,and non sharpening mask algorithms for the system to choose from for processing image data,Finally,the image data is transmitted to the upper computer for display through Ethernet through the written Gig E Vision protocol.In the software design section,transplant the Linux operating system to achieve customized IP cores,image sensors,and other core drivers.Implement control of the camera using the GVCP protocol.In addition,a VDMA driver was designed in terms of data caching to control the data flow between various modules during system operation.Finally,the system was debugged and the debugging results met expectations.The system performance was analyzed through software and hardware comparison,and the difficulties encountered during the design process were summarized and solutions were provided.