Lightweight helmet detection algorithm based on improved YOLOv5

Jianning Li; Junzhao Zhang; Xinyu Zhang; Shuai Wang

doi:10.1117/12.2659641

22 November 2022 Lightweight helmet detection algorithm based on improved YOLOv5

Jianning Li, Junzhao Zhang, Xinyu Zhang, Shuai Wang

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 124751P (2022) https://doi.org/10.1117/12.2659641
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

In the construction process, wearing safety helmet can effectively reduce the injury caused by falling objects and hard objects. In order to detect the wearing of safety helmet during the construction process, a lightweight safety helmet wearing detection algorithm YOLOv5-CS is proposed and applied to the embedded equipment at the construction site. The algorithm is based on the improvement of YOLOv5 target detection algorithm. The improved CAShuffle module is used to form the backbone feature extraction network, which reduces the size of the original algorithm and ensures the detection accuracy of the algorithm; DIoU as the loss function, which makes the algorithm more conducive to detecting small targets such as hard hats; modify dataset, add the dataset on the basis of the original dataset and mark the safety helmet and the anchor frame of the person separately, and judge whether the worker wears the safety helmet by analyzing positional relationship of the identified anchor frame, use the algorithm combining K-means and genetic algorithm to predict the anchor frame of the dataset, and use Mosaic algorithm to enhance the data. The results show that the parameter quantity of YOLOv5-CS algorithm is 2.4M, less than one third of YOLOv5; The average precision decreased by only 4.2%; 640x640 pictures can be recognized at 31 frames per second on Jetson Nano, a embedded platform.

Citation Download Citation

Jianning Li, Junzhao Zhang, Xinyu Zhang, and Shuai Wang "Lightweight helmet detection algorithm based on improved YOLOv5", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 124751P (22 November 2022); https://doi.org/10.1117/12.2659641

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KEYWORDS

Detection and tracking algorithms

Target detection

Safety

Evolutionary algorithms

Feature extraction

Fuzzy logic

Head

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