Low-cost and portable active thermography using cellphone infrared cameras
Bibliographic record
Abstract
Lock-in thermography (LIT) is a non-destructive testing technique with a broad spectrum of applications, spanning from detection of manufacturing defects in industrial samples to early diagnosis of diseases in hard and soft tissues. Nevertheless, commercialization and wide-spread adaption of LIT has long been impeded by the cost (usually $10k-$100k) and size of infrared cameras. In this paper, we demonstrate that this cost and size limitation can be overcome using cell-phone attachment infrared cameras/sensors. Developed low-cost and portable LIT systems use an intensity-modulated near infrared light for illumination while detecting thermal signatures by the low-cost cellphone attachment infrared camera (Seek thermal compact; Android). While the nominal frame rate of camera is less than 9fps, we have deciphered the communication protocol and frame information structure of the camera and set up packets of information and send them to the camera’s default endpoint address and, subsequently, acquire frame data from camera through a corresponding pipe. As such, the developed platform can control camera attributes through a simple USB interface while achieving a stable high frame rate of 33fps. To demonstrate performance of developed low-cost and portable system, two types of LIT experiments were conducted: (i) in response to the recent legalizations of marijuana in Canada, we interrogated photothermal responses of commercially available oral fluid latral flow immunoassays (LFAs), demonstrating reliable detection of THC (the psychoactive substance of cannabis) at concentrations as low as 2 ng/ml. (ii) To demonstrate ability of the system in early detection of dental caries, artificially induced early caries were created on healthy enamel surfaces and imaged with the low cost and portable system at different stages of formation. Results, suggest ability of the system in detection of caries at very early stages when neither x-ray nor visual-tactile inspection can detect them. Both sets of experiments clearly demonstrate the promise of the developed low-cost and portable LIT system in producing reliable LIT images, paving the way for translation of this technology to industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".