Search

ispartof: pages:121340E-1-121340E-10 ispartof: Proceedings of SPIE vol:12134 ispartof: SPIE Photonics Europe 2022 location:Strasbourg, France date:3 Apr - 20 May 2022 status: published

The purpose of this project was to test and implement recent research of polarization and scatter properties that suggest using a cross polarization imaging system to reduce glare artifacts. In particular, the use of this research is to improve the machine vision of apple quality detection in the food industry. The automated measurement system was implemented by acquiring pictures at different angles and different polarization states of apples. The opto-mechanics, system integration, synchronization and data collection are controlled with LabVIEW.

Common illumination systems in short wave infrared (SWIR) hyperspectral imaging (HSI) include direct or indirect tungsten halogen lights. While direct lights provide more radiation onto the samples than dome setups, thus being more energy efficient, the acquired images often suffer from specular reflections and gloss. Glare artifacts in images increase variability in the data limiting the accuracy of machine vision algorithms for defect detection and quality inspection, or even providing false positives. Although domes are known to provide a near Lambertian illumination and glare free images, glossy regions and heterogeneities may remain in the data in practice. More particularly, in the field of fruit and vegetable quality inspection, due to their waxy surface, it remains challenging to design an efficient realistic lighting system. This paper suggests a new approach to optimize the illumination of fruit and vegetables based on measurements of the bidirectional reflectance distribution function (BRDF), shape and Stokes parameters. From these measured values, a BRDF model is loaded into ray-tracing software for realistic illumination engineering in order to determine the most suitable illumination scheme. This concept is applied to apples and a cross polarizer (CP) with freeform optics (FO) optical configuration is proposed, which allows the FO to be optimized to maximize uniformity in the field of view of the imager and removes the parallel polarized gloss on the apples. The performance of this CP illumination system was determined experimentally for a set of apples. This cross polarized (CP) illumination system provided a uniformity (U) of 92% and an efficiency (ν) of 90%, while U = 87% and ν = 14% for an ideal dome configuration when illuminating a rectangular target. The simulated imaged apples with assigned optical properties performed better with CP (U=80%) than when using a dome (U=73%) by 7%. Finally, the sensitivity of the design for the light positioning and spectral tolerance are investigated.

As line scanning short wave infrared (SWIR) hyperspectral imaging (HSI) is a growing field in the food industry, it is important to select efficient illumination designs to image contaminants with high contrast and low noise. Illumination systems can efficiently be compared and optimized through the use of ray tracing simulations. However, these simulations provide illumination patterns in absolute radiometric units while HSI systems typically provide relative measurements. To bridge this gap, a supercontinuum laser and monochromator setup was used in this study to calibrate a SWIR HSI imager in spectral radiometric units. For the radiometric calibration, an integrating sphere (IS) was illuminated with the monochromatic laser light, while both a high sensitivity photodiode and the hyperspectral camera were positioned at different ports of the IS to measure the diffuse light synchronously. For each spectral band, the radiance observed by the imager corresponding to a line was detected using image analysis, while the remainder of the image was used to sample the noise of the sensor. Laser power fluctuations were monitored using a power meter coupled with a thermal sensor, allowing for their correction. As these measurements were time consuming, while InGaAs based sensors are very sensitive to thermal drift, the dark current was sampled frequently to avoid noise time drifts. This approach allowed correcting for 6% of temporal noise fluctuations. A per-pixel linear radiometric model was fitted with an R2 of 0:94±0:3 and used to transfer the measured light distribution of a halogen spot with and without a diffuser into absolute radiometric units. This allowed comparing measurements with the results of ray tracing.

Computer assisted optimal illumination design is crucial when developing cost-effective machine vision systems. Standard local optimization methods, such as downhill simplex optimization (DHSO), often result in an optimal solution that is influenced by the starting point by converging to a local minimum, especially when dealing with high dimensional illumination designs or nonlinear merit spaces. This work presents a novel nonlinear optimization approach, based on design and analysis of computer experiments (DACE). The methodology is first illustrated with a 2D case study of four light sources symmetrically positioned along a fixed arc in order to obtain optimal irradiance uniformity on a flat Lambertian reflecting target at the arc center. The first step consists of choosing angular positions with no overlap between sources using a fast, flexible space filling design. Ray-tracing simulations are then performed at the design points and a merit function is used for each configuration to quantify the homogeneity of the irradiance at the target. The obtained homogeneities at the design points are further used as input to a Gaussian Process (GP), which develops a preliminary distribution for the expected merit space. Global optimization is then performed on the GP more likely providing optimal parameters. Next, the light positioning case study is further investigated by varying the radius of the arc, and by adding two spots symmetrically positioned along an arc diametrically opposed to the first one. The added value of using DACE with regard to the performance in convergence is 6 times faster than the standard simplex method for equal uniformity of 97%. The obtained results were successfully validated experimentally using a short-wavelength infrared (SWIR) hyperspectral imager monitoring a Spectralon panel illuminated by tungsten halogen sources with 10% of relative error.

Visible-near infrared (Vis-NIR) and short wave infrared (SWIR) hyperspectral imaging (HSI) are gaining interest in the food sorting industry. As for traditional machine vision (MV), spectral image registration is an important step which affects the quality of the sorting system. Unfortunately, it currently still remains challenging to accurately register the images acquired with the different imagers as this requires a reference with good contrast over the full spectral range. Therefore, the objective of this work was to develop an accurate high contrast checkerboard over the full spectral range. From the investigated white and dark materials, Teflon and Acktar were found to present very good contrast over the full spectral range from 400 to 2500 nm, with a minimal contrast ratio of 60% in the Vis-NIR and 98 % in the SWIR. The Metal Velvet self-adhesive coating from Acktar was selected as it also provides low specular reflectance. This was taped onto a near-Lambertian polished Teflon plate and one out of two squares were removed after laser cutting the dark coating with an accuracy below 0.1 mm. As standard technologies such as nano-second pulsed lasers generated unwanted damages on both materials, a pulsed femto-second laser setup from Lasea with 60µm accuracy was used to manufacture the checkerboard. This pattern was monitored with an Imec Vis-NIR and a Headwall SWIR HSI pushbroom hyperspectral camera. Good contrast was obtained over the full range of both HSI systems and the estimated effective focal length for the Vis-NIR HSI was determined with computer vision to be 0.5 mm, close to the lens model at high contrast.

In the food industry packaging is often applied to protect the product from the environment, assuring quality and safety throughout shelf life if properly performed. Packaging quality depends on the material used and the closure (seal). The material is selected based on the specific needs of the food product to be wrapped. However, proper closure of the package is often harder to achieve. One problem possibly jeopardizing seal quality is the presence of food particles between the seal. Seal contamination can cause a decreased seal strength and thus an increased packaging failure risk. It can also trigger the formation of microchannels through which air and microorganisms can enter and spoil the enclosed food. Therefore, early detection and removal of seal-contaminated packages from the production chain is essential. In this work, a pulsed-type active thermography method using the heat of the sealing bars as an excitation source was studied for detecting seal contamination. The cooling profile of contaminated seals was recorded. The detection performance of four processing methods (based on a single frame, a fit of the cooling profile, pulsed phase thermography and a matched filter) was compared. High resolution digital images served as a reference to quantify contamination. The lowest detection limit (equivalent diameter of 0.63 mm) and the lowest processing time (0.42 s per sample) were obtained for the method based on a single frame. Presumably, practical limitations in the recording stage prevented the added value of active thermography to be fully reflected in this application.

Alternating Least Squares (ALS) is a blind source separation method commonly used in Chemometrics to simultaneously estimate the absorption spectrum and concentration of the different components in a chemical sample. In this study, the transferability of ALS from Chemometrics to agricultural Remote Sensing is evaluated. Due to the subpixel contribution of background components, spectral unmixing has become an indispensable processing step in the spectral analysis of agricultural areas. Yet, traditional unmixing techniques only allow estimating the sub-pixel cover distribution of the different components, but fail to provide an estimate of the pure spectral signature of the crop. This info is, however, highly valuable as this pure crop signature could be used to monitor the health status of the trees. Here, we anticipate that ALS can provide a solution. ALS estimates both the concentration and the absorption spectra of the different components in a chemical sample and this can easily be translated into estimating both the subpixel cover fraction and spectral signature of the different components in a mixed image pixel. The ALS model was tested on simulated hyperspectral images of Citrus orchards in which ray-tracing software was used to realistically incorporate spectral variability, multiple scattering and shadowing effects. Both the accuracy of the extracted cover fractions and the pure spectral signatures of the crop were assessed, as well as the accuracy with which the biophysical parameters of the trees (i.e. chlorophyll content, leaf water content and Leaf Area Index) could be derived from the extracted crop signature. ALS indeed allowed to simultaneously estimate the subpixel cover distribution (RMSE = 0.05), as well as the pure spectral signatures of the different endmembers (RRMSE < 0.12), and considerably improved the extraction of biophysical parameters (ΔR2 up to 0.43). ALS thus provides a promising new image analysis tool for agricultural remote sensing.

A contact spatially resolved spectroscopy (SRS) setup based on a fiber-optics probe in the Vis/NIR range (400-1000 nm) was developed, calibrated, and validated for its measurements and optical properties estimation by means of a metamodeling method on a set of liquid optical phantoms. Thirty Braeburn apples cultivated in sub-fertilization condition were harvested and measured before and after shelf-life storage (2 weeks at 18 °C) by the setup and were analyzed for quality attributes (firmness and soluble solids contents (SSC)) by destructive reference methods. Estimated optical properties (absorption and reduced scattering coefficients) acquired from SRS measurements at the beginning and the end of the shelf-life indicated changes in chemical composition of the apples. Partial Least Squares Regression (PLSR) was employed to construct calibration models relating the estimated optical properties to the reference quality attributes. The constructed PLS models based on the absorption coefficient spectra gave good prediction performance for the quality attributes of the apples in the validation set with correlation coefficients r of 0.901 and r of 0.844, respectively for SSC and firmness. The obtained results clearly show the potential of the SRS measurements for nondestructive quality evaluation of apples.

A hyperspectral laser scatter imaging (HLSI) system based on a supercontinuum laser in combination with a monochromator has been developed for contactless and non-destructive measuring the ripeness of Braeburn apples. Reflectance images were obtained by a CCD camera at 91 different wavelengths ranging from 550 nm to 1000 nm and transformed into reflectance profiles. A linear function was fitted to the logarithm (log 10 ) of the extracted profiles, resulting in an intercept and a slope. These two parameters were then correlated with apple ripeness parameters such as firmness and soluble solids content (SSC) measured by the reference, destructive methods. Preliminary results showed the potential of slope and intercept to be used as a ripeness indicator. Moreover, during fruit ripening, the new HLSI measurement technique clearly showed the degradation of chlorophyll over time.

In this study, a tool was developed to calculate the bulk optical properties for systems consisting of an absorbing medium and polydisperse spherical particles that can scatter and/or absorb. The developed tool is based on the Mie-theory for monodisperse-spherical absorbing and scattering particles in vacuum. First, the original Mie-theory was expanded to also include physical (real part of refractive index) and chemical (aborption, imaginary part of refractive index) information of the host medium. Secondly, the polydispersity of the spherical particles was taken into account. Since particle size distributions (PSD) are typically continuous distributions and Mie-scattering properties can only be calculated for a monodisperse system, the PSD is fractionated and Mie-scattering properties were calculated for each fraction. These Mie-scattering properties are then combined with the weight for each fraction to derive bulk optical properties. As the number of fractions is unknown and needs to be optimized for each calculation, the developed tool keeps on fractionating until the desired properties (μ abs , μ sca and P 11 ( cos (θ))) converge to stable values. This flexible tool allows for the simulation of the bulk optical properties for a wide range of wavelengths, particle volume fractions, complex refractive indices of both the particles and the medium and PSD's based on normal, lognormal, gamma, bimodal and custom defined functions. This code was successfully validated for the case of a lognormal PSD of scattering spheres in vacuum by comparing the simulated values to those reported in literature. The main novelties of the developed program are the extension of Mie-theory simulations to the case of polydisperse scattering particles in absorbing media and the automatic optimization of the number of PSD fractions needed to converge.

Accurate knowledge of the optical properties of turbid media in the light path is important in NIR absorption spectroscopy of biological tissues where multiple scattering complexes the collected light signals due to the non-uniform tissue architecture. Several approaches such as time resolved spectroscopy and spatially resolved spectroscopy have been proposed to measure the bulk optical properties of turbid media. Among them, double integrating sphere (DIS) measurements are recognized as the "golden standard" for in vitro optical properties measurement of turbid media because of its high accuracy and robustness in different conditions. A DIS system is convenient to measure the in vitro optical properties of turbid media like intralipid solutions and biological tissues, since it measures the diffuse reflectance and transmittance simultaneously. However, DIS measurements have been mostly limited to the optical window region (400-1000 nm) or suffered from low signal levels on the detectors due to the absorption by water in the NIR region. In this study, we developed a DIS system for optical property measurement in the 1300-2350 nm region based on a novel wavelength tunable spectroscopic setup which incorporates a high power broadband supercontinuum laser and a high precision monochromator. With this system, optical properties of intralipid solutions were measured in the wavelength region of 1300-2350nm.

This paper presents an adaptation of the widely accepted Monte Carlo method for Multi-layered media (MCML). Its original Henyey-Greenstein phase function is an interesting approach for describing how light scattering inside biological tissues occurs. It has the important advantage of generating deflection angles in an efficient – and therefore computationally fast- manner. However, in order to allow the fast generation of the phase function, the MCML code generates a distribution for the cosine of the deflection angle instead of generating a distribution for the deflection angle, causing a bias in the phase function. Moreover, other, more elaborate phase functions are not available in the MCML code. To overcome these limitations of MCML, it was adapted to allow the use of any discretized phase function. An additional tool allows generating a numerical approximation for the phase function for every layer. This could either be a discretized version of (1) the Henyey-Greenstein phase function, (2) a modified Henyey-Greenstein phase function or (3) a phase function generated from the Mie theory. These discretized phase functions are then stored in a look-up table, which can be used by the adapted Monte Carlo code. The Monte Carlo code with flexible phase function choice (fpf-MC) was compared and validated with the original MCML code. The novelty of the developed program is the generation of a user-friendly algorithm, which allows several types of phase functions to be generated and applied into a Monte Carlo method, without compromising the computational performance.

Food quality is critically determined by its microstructure and composition. These properties could be quantified noninvasively by means of optical properties (absorption and reduced scattering coefficients) of the food samples. In this research, a spatially-resolved spectroscopy setup based on a fiber-optic probe was developed for acquiring spatiallyresolved diffuse reflectance of three sugar foams with different designed microstructures in the range 500 - 1000 nm. A model for light propagation in turbid media based on diffusion approximation for solving the radiative transport equation was employed to derive optical properties (absorption and reduced scattering coefficients) of these foams. The accuracy of this light propagation model was validated on four liquid phantoms with known optical properties. The obtained results indicated that the optical properties estimation was successfully validated on these liquid phantoms. The estimated reduced scattering coefficients μs' of the foams clearly showed the effect of foaming time on their microstructures. The acquired absorption coefficients μa were also in good agreement with the designed ingredients of these sugar foams. The research results clearly support the potential of spatially-resolved spectroscopy for nondestructive food quality inspection and process monitoring in the food industry.