An in-depth study on blast hole recognition technology in open-pit mines is conducted,proposing and comparing 2 intelligent blast hole recognition methods:a 3D point cloud-based method and a target detection-based method.Experiment verification and performance analyses were carried out in various open-pit mining environments using different visual perception devices.The study reveals that both methods effectively recognize blast holes,with the 3D point cloud-based method achieving a recognition accuracy of 90 %,and the target detection-based method achieving an accuracy of 97.91 %.Detailed comparisons of hardware devices,data processing workflows,and application potential between the 2 methods indicate that when integrated with artificial intelligence technologies,blast hole recognition technology holds significant promise for applications in intelligent on-site bulk charging trucks and other mining equipment.This advancement plays a vital theoretical and practical role in promoting mining technology,enabling unmanned,efficient,and safe mining operations.