Line structured light calibration method and centerline extraction: A review

• Published in: Results in physics Vol. 19; p. 103637
• Main Authors: Xu, Xiaobin, Fei, Zhongwen, Yang, Jian, Tan, Zhiying, Luo, Minzhou
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2020; Elsevier
• Subjects: Calibration method; Centerline extraction; Deep learning; Line structured light; Deep learning; Calibration method; Line structured light; Centerline extraction
• ISSN: 2211-3797; 2211-3797
• DOI: 10.1016/j.rinp.2020.103637

•Line structured light calibration methods are classified into six categories.•The centerline extraction algorithms are categorized into Gray centroid method, Steger algorithm and Skeleton extraction method.•Deep learning denoising method will play an important role in line structured light imaging systems. Line structured light system has made rapid progress in recent years owing to the improvement of camera resolution and image processing technology. The calibration of line structured light system and centerline extraction affect the imaging quality. Hence, numerous innovations have occurred in both line structured light calibration methods and centerline extraction methods. In this paper, key technologies of line structured light calibration are reviewed. Major calibration methods such as vector cross product, linear equation solution, cross ratio invariance, vanishing points and lines, Plücker matrix are analyzed and compared in detail. Methods of centerline extraction are analyzed furthermore. This review concludes with a discussion of the future development of line structured light system, providing a good reference for researchers.