Pipe tread parameters detection based on machine vision

Junpeng Fan; Yanlei Li; Hua Fan; Xinzhong Wang

doi:10.1117/12.2500375

24 July 2018 Pipe tread parameters detection based on machine vision

Junpeng Fan, Yanlei Li, Hua Fan, Xinzhong Wang

Proceedings Volume 10827, Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018); 108271A (2018) https://doi.org/10.1117/12.2500375
Event: Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018), 2018, Shanghai, China

Abstract

Pipe thread plays an important role in modern industry. Traditional methods of pipe thread detection is inefficient and inexact which cannot fulfill the detection needs of modern production.Based on the actual industrial detection requirements, CCD is applied to detect outline dimension of the pipe thread and digital image processing techniques is applied to the image processing of pipe thread in this paper. According to the characteristics of the pipe thread, The filtering and edge detection algorithms in traditional image processing are optimized to realize the accurate image edge contour extraction. By calculating, the geometrical parameters of the pipe thread is obtained, the experimental results show that the improved method can improve the measurement accuracy compared with the traditional method.

Citation Download Citation

Junpeng Fan, Yanlei Li, Hua Fan, and Xinzhong Wang "Pipe tread parameters detection based on machine vision", Proc. SPIE 10827, Sixth International Conference on Optical and Photonic Engineering (icOPEN 2018), 108271A (24 July 2018); https://doi.org/10.1117/12.2500375

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