Enhanced urban drainage pipeline defect detection algorithm based on improved YOLOv8
Drainage pipe system plays a key role in urban management,in order to realize the automated detection of drainage pipe disease.In this paper,we propose a drainage pipe disease de-tection algorithm based on improved YOLOv8.First for the problem of uneven brightness of pipe-line images and poor network generalization ability,data enhancement processing using a combina-tion of Zero-DCE brightness enhancement and image contrast adjustments.Then by adding the Co-ordinate Attention(CA)attention mechanism to the YOLOv8 algorithm,enhancing the algorithm's ability to perceive and capture disease location information,so that the algorithms can better identify minor drainage pipe defects.The experimental results show that compared to the original YOLOv8 algorithm,the improved algorithm increases precision and recall by 5％and 7.9％re-spectively.Compared to the other three networks,the precision and recall are improved by 5.5％,7.6％,2.2％and 7.9％,4.2％,2％respectively.
万方数据
维普
