Image stitching method for defect detection on optical surface based on adaptive registration and fusion

Mengcong Ma; Xi Hou; Mingze Li; Kun Mo; Yue Yang; Mengfan Li; Xiaochuan Hu

doi:10.1117/12.3048142

13 November 2024 Image stitching method for defect detection on optical surface based on adaptive registration and fusion

Mengcong Ma, Xi Hou, Mingze Li, Kun Mo, Yue Yang, Mengfan Li, Xiaochuan Hu

Author Affiliations +

Proceedings Volume 13280, Advanced Optical Manufacturing Technologies and Applications 2024; and Fourth International Forum of Young Scientists on Advanced Optical Manufacturing (AOMTA and YSAOM 2024); 1328015 (2024) https://doi.org/10.1117/12.3048142
Event: Second Conference on Advanced Optical Manufacturing Technologies and Applications & Fourth Forum of Young Scientists on Advanced Optical Manufacturing, 2024, Xi'an, China

Abstract

The large-aperture optical elements are widely applied in various fields, but surface defects of the optical elements will reduce the system performance. Defect detection is one of the main interests of optical measurement research. To achieve defect detection of large-aperture elements, the defect images need to be stitched. This paper proposes a defect image stitching method for large-aperture optical elements based on the adaptive dimensionality reduction registration (ADRR) algorithm and the gradual weighted fusion (GWF) algorithm. The ADRR algorithm adaptively reduces the dimensionality of feature point descriptors extracted by the popular scale-invariant feature transform (SIFT) algorithm, and the low-dimensional descriptors are used to match feature points. The GWF algorithm constructs gradual weight matrices based on the column coordinates of overlapping areas, achieving seamless stitching of defect images. The experimental results show that the ADRR algorithm has a higher effective matching rate and shorter matching time than the SIFT algorithm. The GWF algorithm effectively reduces the interference caused by uneven background brightness. Therefore, the stitching method has good robustness and practicability.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mengcong Ma, Xi Hou, Mingze Li, Kun Mo, Yue Yang, Mengfan Li, and Xiaochuan Hu "Image stitching method for defect detection on optical surface based on adaptive registration and fusion", Proc. SPIE 13280, Advanced Optical Manufacturing Technologies and Applications 2024; and Fourth International Forum of Young Scientists on Advanced Optical Manufacturing (AOMTA and YSAOM 2024), 1328015 (13 November 2024); https://doi.org/10.1117/12.3048142

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KEYWORDS

Image fusion

Image registration

Matrices

Optical components

Defect detection

Optical surfaces

Covariance matrices

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