Design of Epidemic Prevention Detection System Based on Machine Vision

An epidemic prevention detection system based on machine vision is designed in this paper. The system uses STM32F407VGT6 as the control core, uses the MLX90614 sensor to obtain the temperature, uses the average filter algorithm to filter, and performs temperature compensation on the result, which realizes the non-contact temperature measurement function. And then uses the OpenMV machine vision module as the image acquisition and processing module, uses the LBP feature recognition algorithm to detect face images, and the Haar cascade classifier extracts mask features and trains and recognizes them to realize the identity recognition and mask detection functions. Based on theoretical analysis and measured data, the absolute error value of the body temperature measurement of the epidemic prevention detection system is ≤ 1.4
^°
C, which can accurately identify the face identity information and detect whether it meets the epidemic prevention requirements. The system involves MCU programming, image processing, face recognition and other technologies, which can help students better grasp the related knowledge of MCU programming and computer vision, cultivate students' knowledge application ability and practical innovation ability, and meet the cultivation of innovative outstanding engineering and technical talents Requirements.