A real-time vision systemis designed for flapping-wing micro air vehicles (FMAV) withlightweight and high-frequency vibration. The system includes the hardware and software modules. The hardware is consists of a micro camera module, a 5.8GHz transmission module and a wireless image transmission receiving module. And the software modules include two algorithms, one is a real-time video stabilization algorithm based on corner detection, Lucas Kanade optical flow and Kalman low-pass hybrid filtering, and the other one is a person recognition algorithm based on YOLOv3. Flight tests on FMAV with hardware were carried out. The experimental results indicate the video stabilization algorithm can diminish 66.56% vibration of the x-axis and 73.15% vibration of the y-axis. The person recognition algorithm can achieve an accuracy of higher than 96%. The video stabilization algorithm costs 6.33ms and person recognition algorithm costs 20.5ms when the image resolution is 720×480 pixels, thusthe total delay meets the real-time requirements. In conclusion, the design goal of real-time vision system has been achieved.