New algorithm can extract hypectral info from conventional photos

Professionals in Agriculture, Defense and Security, Environmental Monitoring, Food Quality Analysis, Industrial Quality Control, and Medical Diagnostics COUNTICS COUNTICS COUNTICS COUNEFITICS CONFITICS CONFITICS CONFITICS COME New Possibilites of Conventional Photography for Optical Spectroscopy and Hyperspectral imaging.

Young Kim, Purdue University Professor, University Faculty Scholar and Showalter Faculty Scholar, and Postdoctoral Research Associate Semin of the weldon school of the weldon school of elected algorithm that recovers detailed spectral information from photos photographs taken by conventional cameras. The Research Combines Computer Vision, Color Science and Optical Spectroscopy.

“A photo is more than just an image; it contains abundant hypertral information,” Kim said. “We are one of the pioneering research groups to integrate computational spectrometry and spectroscopic analyses for biomedical and other applications.”

A paper about the team’s research has been published in the journey IEEE transactions on image processing,

Kim disclosed the innovation to the purdue innovates office of technology commercialization, which has applied for a patent to Protect the Intellectual Property.

Generalizability and Simplicity

Kwon said the work emphasizes recovering the arbitrary spectrum of a sample rather than solely related on specific data-Dr. Driven Learning or pretrained algorithms, which excel on Samples.

The team’s method uses an algorithmically designed color chart and device-informed computation to recover Spectral Information from RGB Values ​​Acquuired Using Conventional Cameras, Such Ass Off-the-shhelf smartphones.

“Importantly, the spectral resolution -aeround 1.5 nanometers – is highly comparable to that of scientific spectrometers and hyperspectral images,” Kwon said. “Scientific-grade spectrometers have finspel resolution to distinguish narrow spectral features. Even Small Wavelength Shifts can lead to different interpretations. “

Kim said one advantage the purdue method has over traditional technology is its algorithmic generalizability.

“From an algorithmic standpoint, to the best of our knowledge, our paper presents the first computational spectrometry method with 1.5-nm spectral resolution using a photogitrary sample Without relaying on Specific Training Data or PredeterMined Algorithms, “He said.

Kwon Said Another Advantage of the Purdue Method is its hardware simplicity.

“Many Mobile Spectrometers Require Additional Accessories and Bulky Components as Mandatory Attachments to Smartphones,” He Said. “In contrast, our method levels the buy-in camera of the smartphone.

Validation and next steps

Kim and kwon are currently using the algorithm as a foundation for digital and mobile health applications in bot domestic and resource-limited settings.

“Photography is central to these applications, but color distortion has been posed a person challenge, which is why we are focusing on these settings,” Kim said. “This algorithm provides a Basis for Quantifying and Correcting Colors, Enhancing The Reliability of Medical Diagnostics.”