Research on Traditional Image Segmentation Method Based on Oil Drilling Pipe Defects

Abstract

This study explores the feasibility and efficacy of conventional image seg-mentation technology in diagnosing failures in oil drilling pipe images. Simultaneously, it envisions an intelligent approach to diagnose defects in oil drilling pipes. The present paper examines and scrutinizes traditional image segmentation methods in light of the characteristics of oil drilling pipe defect images. It devises experiments tailored for these defect images and employs various traditional image segmentation methods to facilitate comparison and evaluation. The experimental findings illustrate that the traditional image segmentation methods possess a discernible impact on detecting defects in oil drilling pipes, with the image segmentation effect based on the Canny operator method of edge detection proving to be the most effective. The experiments are specifically devised for defective images of oil drilling pipes, utilizing diverse traditional image segmentation methods for comparison and evaluation. The experimental results demonstrate that the traditional image segmentation methods exhibit a certain degree of efficacy in detecting defects in oil drilling pipes, with the image segmentation effect based on the Canny operator method of edge detection being the most optimal.