The Spectrum of Light Emitted by LED Using a CMOS Sensor-Based Digital Camera and Its Application

Park, Hyeon-Woo; Choi, Jiwon; Choi, Jiyoung; Joo, K. K.; Kim, Nari

doi:10.3390/s22176418

Cited by 2 publications

(2 citation statements)

References 30 publications

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“…Spectrophotometers’ shortcomings in wide surfaces have been adequately overcome in the past years by digital cameras, which have proven to be a low-cost alternative to spectrophotometers for colorimetry measurements. − Complete multicolored or nonhomogeneously colored surfaces can be recorded and simultaneously analyzed pixel by pixel. Moreover, due to their technological advancements and rapid price decline, even smartphone cameras could become an acceptable alternative. ,− Image acquisition in these devices relies on three sensors, with a nonlinear response, for the three wavelength ranges that correspond to red, green, and blue.…”

Section: Introductionmentioning

confidence: 99%

Neural Network-Based Digital Camera Spectrophotometer: Application to Chromogenic Technologies Characterization

Cánovas-Saura,

Serrano-Luján,

Beltrán

et al. 2024

ACS Appl. Opt. Mater.

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In this work, a neural-network-assisted procedure for transmittance spectral reconstruction from digital images is proposed. This allows the use of digital cameras as visible range spectrophotometers. The neural network is able to reconstruct a whole visible spectrum (in the range of 400 to 700 nm) from three-color coordinates. Precise color coordinates obtained from digital images are shown for different lighting conditions and file formats. Through a two-stage training of the neural network, consisting in a first broad gamut of transmittance spectral data set (3660 spectra) and a subsequent fine retraining data set (915 additional spectra), reconstruction of visible spectra with mean absolute errors below 2.15% (compared with measured spectra through a conventional spectrophotometer) is achieved. The possibility of simultaneous transmittance quantification over extended areas through digital imaging (statically or dynamically through video acquisition), which presently is restricted to a few mm 2 in conventional spectrophotometers, opens the way for improved colorimetry and visible range spectrophotometry. This could result in particular usefulness in the field of chromogenic technologies, where an adequate quantification of the homogeneity of color transitions over big surfaces is a key feature for a proper technological advance. For this purpose, the experimental application of the proposed system as a spectrophotometer was assessed through a complete optical characterization of four electrochromic polymers, obtaining the most relevant performance parameters (optical contrast, switching speed, and cycling stability). Excellent agreement between the values obtained from measured and reconstructed spectra proves the viability of the proposed tool, constituting a lowcost reliable alternative that overcomes some of the limitations of present conventional spectrophotometers.

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Section: Introductionmentioning

confidence: 99%

Neural Network-Based Digital Camera Spectrophotometer: Application to Chromogenic Technologies Characterization

Cánovas-Saura,

Serrano-Luján,

Beltrán

et al. 2024

ACS Appl. Opt. Mater.

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“…In the eighth paper, by Park et al [ 8 ], the authors introduced a digital photo image analysis in color space to estimate the spectrum of fluor components dissolved in a liquid scintillator sample through the hue and wavelength relationship. Complementary metal oxide semiconductor (CMOS) image sensors with Bayer color filter array (CFA) technology in the digital camera were used to reconstruct and decode color images.…”

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confidence: 99%