Adaptive Reflection Detection and Control Strategy of Pointer Meters Based on YOLOv5s

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 5; p. 2562
• Main Authors: Liu, Deyuan, Deng, Changgen, Zhang, Haodong, Li, Jinrong, Shi, Baojun
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 25.02.2023; MDPI
• Subjects: Accuracy; Algorithms; Analysis; Data mining; Deep learning; inspection robot; k-means clustering algorithm; pose transformation; reflection detection; Robots; YOLOv5s; China; Pennsylvania; reflection detection; pose transformation; k-means clustering algorithm; inspection robot; YOLOv5s

Reflective phenomena often occur in the detecting process of pointer meters by inspection robots in complex environments, which can cause the failure of pointer meter readings. In this paper, an improved k-means clustering method for adaptive detection of pointer meter reflective areas and a robot p...