As an important data to be retained and verified,railway hidden engineering images often contain massive engineering data.The existing image data management system provides an important platform for engineering acceptance.In order to improve the efficiency of engineering image review,realize less human hidden engineering review and standardize image acceptance management,a relatively mature target detection model YOLOv8 was selected,and an executable loss function CIOU was established to ensure the error direction propagation process,which was used to accurately identify acceptance targets such as acceptance personnel,identification plates and measuring scale images.The accuracy rate,recall rate,weighted harmonic average F1 of accuracy rate and recall rate were selected as the evaluation indexes of the model.The experimental results show that the acceptance personnel and the identification plate respectively reach more than 90%,and the detection accuracy of the measuring scale is more than 80%,and it has better target detection effect than other models.Hidden engineering automatic recognition processing software can serve the automatic recognition of engineering image inspection elements.The research results can provide reference for standardizing the inspection and acceptance management of railway construction image and the intelligent inspection and acceptance management of hidden engineering.
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