A robust algorithm for weld seam extraction based on prior knowledge of weld seam

Zhen Ye, Gu Fang, Shanben Chen, Mitchell Dinham

Research output: Contribution to journalArticlepeer-review

48 Citations (Scopus)

Abstract

Purpose - This paper aims to develop a method to extract the weld seam from the welding image. Design/methodology/approach - The initial step is to set the window for the region of the weld seam. Filter and edge-operator are then applied to acquire edges of images. Based on the prior knowledge about characteristics of the weld seam, a series of routines is proposed to recognize the seam edges and calculate the seam representation. Findings - The proposed method can be used to extract seams of different deviations from noise-polluted images efficiently. Besides, the method is low time-consuming and quick enough for real time processing. Practical implications - Weld seam extraction is the key problem in passive vision based seam tracking technology. The proposed method can extract the weld seam even when the image is noisy, and it is quick enough to be applied in seam tracking technology. The method is expected to improve seam tracking results. Originality/value - A useful method is developed for weld seam extraction from the noise-polluted image based on prior knowledge of weld seam. The method is robust and quick enough for real time processing.
Original languageEnglish
Pages (from-to)125-133
Number of pages9
JournalSensor Review
Volume33
Issue number2
DOIs
Publication statusPublished - 2013

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