Article Details

Title · Authors · Abstract · Keywords · DOI · References

Sub-pixel Extraction Method for Light Stripe Center on Metal Surface Based on K-means Clustering

JIN Zhenzhong

(School of Mechanical Engineering, Nanjing Institute of Technology, Nanjing 211167, China)

Section：Computer Technology · Vol. 2025, Issue 5 · Pages：115-118,124 · 2096-4706（2025）05-0115-05 · CLC number：TP391 · Document code：A · DOI：10.19850/j.cnki.2096-4706.2025.05.021

Abstract

Line structured light vision sensing is widely used in the field of weld detection and tracking. To address the problem of reflective interference on the metal surface during weld detection, a sub-pixel extraction method for the light stripe center based on K-means clustering is proposed. Firstly, median filtering is applied to process the collected structured light stripe images to remove high-frequency noise. Then, the K-means clustering algorithm is used to separate the light stripe from the background, avoiding the interference of background diffuse light spots. The opening operation is performed on the light stripe images after clustering segmentation to smooth the edges of the light stripe and remove the burrs. Finally, the adaptive two-dimensional gray-scale center of gravity method is used to extract the sub-pixel center of the light stripe. The standard deviation of the linear distance between the extracted centerline and the line fitted by the least squares method for the set of center points is 0.157 0 pixels, and the program running time is 0.251 8 s.

Keywords

line structured light; center extraction; image clustering segmentation; gray-scale center of gravity method

References

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About the authors

Jin Zhenzhong (1998-), male, Han ethnicity, from Hefei, Anhui Province, is currently pursuing a master's degree in machine vision.