Image recognition method for dangerous behavior of non-stop construction personnel in large airports

Abstract

It is crucial to ensure the safety of personnel and prevent unauthorized intrusion in the non-stop construction area of large airports. This study proposes an image recognition method for dangerous behavior of non-stop construction personnel in large airports based on infrared imaging technology. Using infrared imaging technology to collect visual information of images of non-stop construction personnel in large airports, and analyzing images using structured similarity features; Based on supervised comparative learning, the method of extracting backbone features is adopted to achieve dynamic feature segmentation and reconstruction processing; Based on ambiguity analysis, extract the edge bounding contour features of personnel and identify dangerous intrusion behaviors of personnel. Through experimental verification, this method has high accuracy in detecting personnel's dangerous intrusion behavior.