A Comparative Evaluation of Spectral Reflectance Representations for Spectrum Reconstruction, Interpolation and Classification

Huynh, Cong Phuoc; Robles-Kelly, Antonio

doi:10.1109/cvprw.2013.56

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…Due to the high dimensional nature of spectral data, many classical algorithms in pattern recognition and machine learning have naturally been borrowed and adapted to perform feature extraction and classification and to shorten the calculation time [22][23][24] . To accurately analyse large high-resolution HSI datasets, using complex light transport models to quantify the blood volume and oxygenation, is however computationally demanding.…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal skin blood volume and saturation estimation using a multispectral snapshot imaging camera

2017

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Hyperspectral imaging (HSI) can estimate the spatial distribution of skin blood oxygenation, using visible to near-infrared light. HSI oximeters often use a liquid-crystal tunable filter, an acousto-optic tunable filter or mechanically adjustable filter wheels, which has too long response/switching times to monitor tissue hemodynamics. This work aims to evaluate a multispectral snapshot imaging system to estimate skin blood volume and oxygen saturation with high temporal and spatial resolution. We use a snapshot imager, the xiSpec camera (MQ022HG-IM-SM4X4-VIS, XIMEA®), having 16 wavelength-specific Fabry-Perot filters overlaid on the custom CMOS-chip. The spectral distribution of the bands is however substantially overlapping, which needs to be taken into account for an accurate analysis. An inverse Monte Carlo analysis is performed using a two-layered skin tissue model, defined by epidermal thickness, haemoglobin concentration and oxygen saturation, melanin concentration and spectrally dependent reduced-scattering coefficient, all parameters relevant for human skin. The analysis takes into account the spectral detector response of the xiSpec camera. At each spatial location in the field-of-view, we compare the simulated output to the detected diffusively backscattered spectra to find the best fit. The imager is evaluated for spatial and temporal variations during arterial and venous occlusion protocols applied to the forearm. Estimated blood volume changes and oxygenation maps at 512x272 pixels show values that are comparable to reference measurements performed in contact with the skin tissue. We conclude that the snapshot xiSpec camera, paired with an inverse Monte Carlo algorithm, permits us to use this sensor for spatial and temporal measurement of varying physiological parameters, such as skin tissue blood volume and oxygenation.

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Section: Introductionmentioning

confidence: 99%

Spatial and temporal skin blood volume and saturation estimation using a multispectral snapshot imaging camera

2017

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“…Although every person has skin, each person's skin is structurally unique. [12][13][14] Skin layers vary in thickness, interfaces between skin layers have different undulations and other characteristics, the amounts of collagen fibers and elastic fibers in the skin layers differ, and capillary bed density and location differ. [15][16][17][18][19][20] Cell size and density within the skin layers, as well as the chemical makeup of these layers, also vary from person to person.…”

Section: Introductionmentioning

confidence: 99%

Novel wearable-type biometric devices based on skin tissue optics with multispectral LED–photodiode matrix

Kim

Kang

et al. 2017

Jpn. J. Appl. Phys.

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In this study, we examined the possibility of using a multispectral skin photomatrix (MSP) module as a novel biometric device. The MSP device measures optical patterns of the wrist skin tissue. Optical patterns consist of 2 ' 8 photocurrent intensities of photodiode arrays, which are generated by optical transmission and diffuse reflection of photons from LED light sources with variable wavelengths into the wrist skin tissue. Optical patterns detected by the MSP device provide information on both the surface and subsurface characteristics of the human skin tissue. We found that in the 21 subjects we studied, they showed their unique characteristics, as determined using several wavelengths of light. The experimental results show that the best personal identification accuracy can be acquired using a combination of infrared light and yellow light. This novel biometric device, the MSP module, exhibited an excellent false acceptance rate (FAR) of 0.3% and a false rejection rate (FRR) of 0.0%, which are better than those of commercialized biometric devices such as a fingerprint biometric system. From these experimental results, we found that people exhibit unique optical patterns of their inner-wrist skin tissue and this uniqueness could be used for developing novel high-accuracy personal identification devices.

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Strategies for Resolving Camera Metamers Using 3+1 Channel

Prasad

2016

2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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A Comparative Evaluation of Spectral Reflectance Representations for Spectrum Reconstruction, Interpolation and Classification

Cited by 4 publications

References 25 publications

Spatial and temporal skin blood volume and saturation estimation using a multispectral snapshot imaging camera

Spatial and temporal skin blood volume and saturation estimation using a multispectral snapshot imaging camera

Novel wearable-type biometric devices based on skin tissue optics with multispectral LED–photodiode matrix

Strategies for Resolving Camera Metamers Using 3+1 Channel

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