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8 April 2016 A novel background subtraction technique based on grayscale morphology for weld defect detection
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Abstract
Optical inspection is a non-destructive quality monitoring technique to detect defects in manufactured parts. Automating the defect detection, by application of image processing, prevents the presence of human operators making the inspection more reliable, reproducible and faster. In this paper, a background subtraction technique, based on morphological operations, is proposed. The low-computational load associated with the used morphological operations makes this technique more computationally effective than background subtraction techniques such as spline approximation and surface-fitting. The performance of the technique is tested by applying to detect defects in a weld seam with non-uniform intensity distribution where the defects are precisely segmented. The proposed background subtraction technique is generalizable to sheet, surface, or part defect detection in various applications of manufacturing.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Masoumeh Aminzadeh and Thomas Kurfess "A novel background subtraction technique based on grayscale morphology for weld defect detection", Proc. SPIE 9804, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure 2016, 98041E (8 April 2016); https://doi.org/10.1117/12.2223262
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