Design and implementation of safety helmet detection system based on computer vision

Huifen Wu; Zhiquan Liao

doi:10.1117/12.2626829

20 December 2021 Design and implementation of safety helmet detection system based on computer vision

Huifen Wu, Zhiquan Liao

Proceedings Volume 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021); 121550R (2021) https://doi.org/10.1117/12.2626829
Event: International Conference on Computer Vision, Application, and Design (CVAD 2021), 2021, Sanya, China

Abstract

Production safety is an eternal topic in industrial production. It is very important to detect the wearing condition of workers' safety helmets in construction sites to reduce the occurrence of production accidents. We collected pictures of construction site workers' hard hats, and then preprocessed and labeled them to train and test our models. In this paper, object detection algorithm based on convolutional neural network (YOLOv3) is used to detect whether workers wear safety helmets. Then, the model is improved and optimized by data enhancement, modifying training parameters and increasing training times. Experimental results show that the accuracy of the model is 83.48%, which indicates that the model has good generalization ability and can obtain better real-time recognition and detection effect under the condition of guaranteeing accuracy.

Citation Download Citation

Huifen Wu and Zhiquan Liao "Design and implementation of safety helmet detection system based on computer vision", Proc. SPIE 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021), 121550R (20 December 2021); https://doi.org/10.1117/12.2626829

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