Evidence map›Paper›PMID 39204790›Full record

ArticleSensors (Basel, Switzerland)2024

Large-Area Film Thickness Identification of Transparent Glass by Hyperspectral Imaging.

Shuan-Yu Huang, Riya Karmakar, Yu-Yang Chen, Wei-Chin Hung, Arvind Mukundan, Hsiang-Chen Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Shuan-Yu HuangDepartment of Optometry, Central Taiwan University of Science and Technology, Taichung 40601, Taiwan.
Riya KarmakarDepartment of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan.
Yu-Yang ChenDepartment of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan.
Wei-Chin HungDepartment of Physics, R. O. C. Military Academy, Kaohsiung 83020, Taiwan.
Arvind MukundanDepartment of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan.ORCID 0000-0002-7741-3722
Hsiang-Chen WangDepartment of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan.ORCID 0000-0003-4107-2062

Funding

Kaohsiung Armed Forces General Hospital 111-034National Science and Technology Council of Taiwan NSTC 112-2221-E-194-036 and NSTC 112-2222-E-194-002
6 · The paper itself

Abstract

This study introduces a novel method for detecting and measuring transparent glass sheets using hyperspectral imaging (HSI). The main goal of this study is to create a conversion technique that can accurately display spectral information from collected images, particularly in the visible light spectrum (VIS) and near-infrared (NIR) areas. This technique enables the capture of relevant spectral data when used with images provided by industrial cameras. The next step in this investigation is using principal component analysis to examine the obtained hyperspectral images derived from different treated glass samples. This analytical procedure standardizes the magnitude of light wavelengths that are inherent in the HSI images. The simulated spectral profiles are obtained using the generalized inverse matrix technique on the normalized HSI images. These profiles are then matched with spectroscopic data obtained from microscopic imaging, resulting in the observation of distinct dispersion patterns. The novel use of images coloring methods effectively displays the thickness of the glass processing sheet in a visually noticeable way. Based on empirical research, changes in the thickness of the glass coating in the NIR-HSI range cause significant changes in the transmission of infrared light at different wavelengths within the NIR spectrum. This phenomenon serves as the foundation for the study of film thickness. The root mean square error inside the NIR area is impressively low, calculated to be just 0.02. This highlights the high level of accuracy achieved by the technique stated above. Potential areas of investigation that arise from this study are incorporating the proposed approach into the design of a real-time, wide-scale automated optical inspection system.

Indexed as

hyperspectral imagingnear-infraredthickness estimationtransparent glass

Identifiers

PMID39204790
PMCPMC11359249

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.