Evidence map›Paper›PMID 36772321›Full record

ArticleSensors (Basel, Switzerland)2023

Automatic Thinning Detection through Image Segmentation Using Equivalent Array-Type Lamp-Based Lock-in Thermography.

Seungju Lee, Yoonjae Chung, Chunyoung Kim, Wontae Kim

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Seungju LeeDepartment of Future Convergence Engineering, Kongju National University, 1223-24 Cheonan-Daero, Seobuk-gu, Cheonan-si 31080, Republic of Korea.ORCID 0000-0002-7384-9158
Yoonjae ChungEco-Sustainable Energy Research Institute, Kongju National University, 1223-24 Cheonan-Daero, Seobuk-gu, Cheonan-si 31080, Republic of Korea.
Chunyoung KimenesG, 8, Techno 10-ro, Yuseong-gu, Daejeon 34026, Republic of Korea.ORCID 0000-0002-4602-8696
Wontae KimDepartment of Future Convergence Engineering, Kongju National University, 1223-24 Cheonan-Daero, Seobuk-gu, Cheonan-si 31080, Republic of Korea.ORCID 0000-0002-9547-3868

Funding

Ministry of Education, Science and Technology S3249835National Research Foundation of Korea NRF-2022R1A2C1011413
6 · The paper itself

Abstract

Among the non-destructive testing (NDT) techniques, infrared thermography (IRT) is an attractive and highly reliable technology that can measure the thermal response of a wide area in real-time. In this study, thinning defects in S275 specimens were detected using lock-in thermography (LIT). After acquiring phase and amplitude images using four-point signal processing, the optimal excitation frequency was calculated. After segmentation was performed on each defect area, binarization was performed using the Otsu algorithm. For automated detection, the boundary tracking algorithm was used. The number of pixels was calculated and the detectability using RMSE was evaluated. Clarification of defective objects using image segmentation detectability evaluation technique using RMSE was presented.

Indexed as

array-type lampautomatic detectiondetectability evaluationimage segmentationlock-in thermographymorphology operation

Identifiers

PMID36772321
PMCPMC9921815

What OpenQuestion holds

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Registered trials

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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.