ArticlePloS one2020
Accurate device-independent colorimetric measurements using smartphones.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Additive Manufacturing of Thermochromic Chitosan Hydrogels for Battery-Free Colorimetric Thermal Indication.Polymers · 2026Article
- PCDA-EDA Colorimetric Nanofiber Sensor for Rapid Visual GHB Screening: Linker Reassignment and Scalable Fabrication.Biosensors · 2026Article
- Smartphone-based optical and spectroscopic sensors for food safety monitoring: principles, applications, and future directions.Mikrochimica acta · 2026Review
- Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging.Science advances · 2025Article
- Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone-Based Reading System.Annals of laboratory medicine · 2025Article
- Color discrepancy of single-shade composites at different distances from the interface measured using cell phone images.Restorative dentistry & endodontics · 2024Article
- Scars.Nature reviews. Disease primers · 2023Review
- Assessment of bilirubin levels in patients with cirrhosis via forehead, sclera and lower eyelid smartphone images.PLOS digital health · 2023Article
- A novel smartphone scleral-image based tool for assessing jaundice in decompensated cirrhosis patients.Journal of gastroenterology and hepatology · 2023Article
- Feasibility of smartphone colorimetry of the face as an anaemia screening tool for infants and young children in Ghana.PloS one · 2023Article
- A novel systems solution for accurate colorimetric measurement through smartphone-based augmented reality.PloS one · 2023Article
- Secure Food-Allergen Determination by Combining Smartphone-Based Raw Image Analyses and Liquid Chromatography-Mass Spectrometry for the Quantification of Proteins Contained in Lateral Flow Assays.Analytical chemistry · 2022Article
- Smartphone-based imaging systems for medical applications: a critical review.Journal of biomedical optics · 2021Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smartphones provide an ideal platform for colorimetric measurements due to their low cost, portability and image quality. As with any imaging-based colorimetry system, ambient light and device variations introduce error which must be dealt with. We propose a novel processing method consisting of a one-time calibration stage to account for inter-phone variations, and an innovative use of ambient light subtraction with image pairs to account for variation in ambient light. Data collection is kept very simple, making it particularly useful for use in the field, since nothing additional is required in the images. Ambient subtraction is first demonstrated for a range of colors and phones (Samsung S8 and LG Nexus 5X), and the Subtracted Signal to Noise Ratio (SSNR) is defined as a metric for assessing whether an image pair is appropriate at the time of image capture. The experimentally determined SSNR threshold below which to suggest retaking the images is 3.4. The classification accuracy for results using the proposed calibration pipeline is then compared to the simplest image metadata-based alternative and is found to be greatly superior. Finally, a custom colorcard is shown to improve the accuracy of device-independent results for known smaller ranges of colors over a standard colorcard, making this a possible application-specific modification to the overall processing pipeline.
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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.