Safety Helmet Wearing Detection Based on Image Processing and Deep Learning

摘要

The environment of the steel factory workshop is complex, and there may be a variety of unexpected potential dangers, so wearing a helmet to enter the workshop is a prerequisite for the factory. In order to supervise this situation, it is necessary for employees to wear helmets for testing, which is a key part of the overall intelligent monitoring system for steel plant personnel. In this paper, through the crawler to collect high-definition employees wearing helmets and no helmet pictures, using manual labeling, proposed a helmet detection framework based on computer vision deep learning detection framework Faster-RCNN. The actual testing results produce convincing experimental results, which proves the effectiveness and practicability of the proposed framework.