In recent years, the popularization of the application of visualization equipment has made a huge image information resources. As an extremely important information, image information is closely related to the whole human life. At the same time, the vigorous development of our country's engineering construction industry has led a rapid increase in the number of construction sites, and the importance of construction safety has become an urgent problem to be solved. How to make full use of existing information resources to realize the detection and warning of hidden dangers in construction safety caused by non-compliant fence placement, A method for detecting compliance of fences based on Open CV is proposed. Open CV is used to detect the compliance of the construction site fence placement on the massive video image information collected by the current power construction site visualization equipment. Through the processing of the construction site pictures, the target fence part in the image is first preprocessed, and the connected area analysis algorithm is combined with the region growth algorithm to realize the extraction of the fence part of the fence group and the preliminary judgment of the existence of the gap. Then, a classifier dedicated to detecting fence gaps is trained to re-detect the fence groups with gaps, and the number of gaps in the detection results is counted. By testing the samples of the test set, analyzing the detection results of the classifier, summarizing and solving the problem of inaccurate detection results of the classifier, and retraining and optimizing the classifier, the algorithm can finally realize the judgment of the compliance of fence placement. Through the application of a series of image processing algorithms and the training of special classifiers, the number of gaps is used as a breakthrough for judging whether the fences are placed in compliance. It expands the idea for the detection of such characteristic fuzzy objects.