• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.3
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• pp.314-319
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• 2008

Near infrared (NIR) spectroscopy was used to classify normal and artificially aged nonviable corn (Zea mays L., cv. 'Suwon19') seeds. The spectra at 1100-2500nm were scanned with normal and artificially aged single seeds and analyzed by principle component analysis (PCA). To discriminate normal seeds from artificially aged seeds, a calibration modeling set was developed with a discriminant partial least square 2 (PLS 2) method. The calibration model derived from PLS 2 resulted in 100% classification accuracy of normal and artificially aged (aged) seeds from the raw, the 1st and 2nd derivative spectra. The prediction accuracy of the unknown normal seeds was 88, 100 and 97% from the raw, the $1^{st}$ and $2^{nd}$ derivative spectra, and that of the unknown aged seeds was 100% from all the raw, the $1^{st}$ and $2^{nd}$ derivative spectra, respectively. The results showed a possibility to separate corn seeds into viable and non-viable using NIR spectroscopy.

• Proceedings of the PSK Conference
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• 2002.10a
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• pp.399.3-399.3
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• 2002

Near-infrared (NIR) system was used to determine rapidly and simply indomethacin in buffer solution for a dissolution test for tablets and capsules. Indomethacin standards were prepared ranging from 10 to 50ppm using mixture of phosphate buffer(pH 7,2) and water(1:4), The near infrared(NIR) transmittance spectra of indomethacin standard solutions were collected by using a quartz cell in 1 mm and 2mm pathlength, Partial least-square regression (PLSR) was explored to develop calibration models over the spectral range 1100-1700nm. (omitted)

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.37-42
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• 2009

This study extracted Near Infrared (NIR) band using Image Processing Technology (IPT), and calculated Normalized Difference Vegetation Index (NDVI). Aerial photography from Daum portal in combination with high resolution satellite image was employed to improve vegetation sensitivity by extracting NIR band and calculating NDVI with comparison to QuickBird result. The extracted NIR band and NDVI through IPT presented similar distribution pattern. In addition, a regression analysis by land cover character showed high correlation paddy and forest Therefore, this approach could be acceptable to acquire vegetation environment information.

• Proceedings of the PSK Conference
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• 2002.10a
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• pp.400.2-400.2
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• 2002

Near-infrared(NIR) reflectance spectroscopy was employed to qualify various ploymorphs. We collected 8 potential polymorphs forms of Medicine T for this study. Near-infared spectra of the powder samples contained in glass vials were obtained over the wavelength region of 1100-1750nm. There were the peak around 1560nm in the 6 spectra among 8 spectra. Principal component analysis(PCA) has been performed to examine the qualitative difference of 8 polymorphs PC space. (omitted)

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.115-123
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• 2015

The infrared light is known to be less dependent on background light compared to the visible light, and thus many applications such as remote sensing and image surveillance use the infrared image. Similar to color images, infrared images can also be degraded by hazy weather condition, and consequently the performance of the infrared image-based applications can decrease. Nevertheless, infrared image dehazing has not received significant interest. In this paper, we analyze the characteristic of infrared images, especially near-infrared (NIR) images, and present an NIR dehazing algorithm using the analyzed characteristics. In particular, a machine learning framework is adopted to obtain an accurate transmission map and several post-processing methods are used for further refinement. Experimental results show that the proposed NIR dehazing algorithm outperforms the conventional color image dehazing method for NIR image dehazing.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1082-1082
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• 2001

Extrusion is one of the most important processes in polymer industry. The characterization of the polymer melt during processing will improve this process noticeably, One possibility of characterizing the actual processed polymer melt is the inline near infrared (NIR) spectroscopy, With this method several polymer properties can be observed during processing, e.g. composition, moisture ormechanical properties of the melt. For this purpose probes for transmission and reflection measurements have been developed, withstanding the high temperatures and pressures appearing during extrusion process (tested up to 300$^{\circ}C$ and 10 ㎫). For the transmission system an optical bypass was developed to eliminate disturbing spectral influences and hence increase the long term stability, which is the prerequisite for an industrial application. Measurements in transmission and reflection produced comparable results (or blending processes, where the prediction error was less than 1%. An optimum RMSEP of only 0.24% was found for preprocessed polymer blends measured in transmission on a laboratory extruder. A transflection measurement allowed for the first time the recording of relevant NIR-spectra in the screw area of an extruder. The application to a (PE+PP) blending process delivered promising results. This new measurement mode allows the observation of the ongoing processes within the screw area, which is of maximum Interest for reactive extrusion processes. Due to economic reasons the calibration transfer between different extrusion systems is also of high importance. Investigations on simulated and real-world spectra showed that a calibration transfer is possible. A new method alternatively to the well-known direct standardization procedures was developed, which is based on an automatic data pretreatment. This procedure delivers comparable results for the calibration transfer. Overall this paper presents concepts, components and algorithms for the inline near infrared (NIR) spectroscopy for polymer extrusion, which allows the use of it in a real industrial extrusion process.

• Near Infrared Analysis
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• v.2 no.1
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• pp.55-58
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• 2001

The object of this work was to investigate the influence of growing district and harvest year on calibration for sweetness (Brix) determination of Fuji apple fruit using near infrared (NIR) reflectance spectroscopy, and to develop the robust calibration across these variation. The calibration models was based on wavelength range of 1100∼2500 nm using a stepwise multiple linear regression. A calibration model by sample set of one growing district was not transferable to other growing districts. The combined calibration (data of three growing districts) predicted reasonable well against a population set drawn from all growing districts (SEP=0.69, Bias=0.075). A calibration model by sample set of one harvest year was not also transferable to other harvest years. The combined calibration (data of three harvest years) predicted well against a population set drawn from all harvest years (SEP=0.53, Bias=0.004).

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.2102-2102
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• 2001

Near infrared, diffuse reflectance spectroscopy has shown significant potential for in vitro and in vivo assessment of metabolic status. However, the complexity of living samples can lead to ambiguous results. This presentation will focus on methods that provide controls for scattering and absorption estimation in tissue. For robust estimations, normalization procedures will be shown which can greatly improve interpretability of results. Normalization based on time, location and spectral property will be shown with data from models, tissue phantoms and in vivo measurements. In particular, interpretation of NIR spectra associated with major respiratory constituents will be examined. Measurement of constituents such as hemoglobin, myoglobin, tissue edema, and lactate will be shown. Results suggest that NIR may provide a valuable tool for physiological monitoring in critical care research and practice.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1525-1525
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• 2001

Non-destructive determination of soluble solids(Brix) in harvested fruits using near infrared(hereafter, NIR) spectroscopy has been reported by many researchers. We have just reported on non-destructive estimation of Brix in harvested melons using a NIR Systems Model 6500 spectrophotometer(Ito et al., 2000). There is a melon cultivar that is difficult to judge the harvest time from the external appearance. If we can determine Brix in growing fruits non-destructively in the field, immature fruits will not be harvested. A portable m spectrophotometer for field use has been just developed by Kubota Corporation. The spectral data of growing melons were measured by the portable spectrophotometer. A commercial program was used for multiple linear regression analysis. Brix in growing melons could be estimated by a multiple regression equation calibrated with harvested melons. Absorbances of 906 and 874 nm were included as the independent variables in the multiple regression equation, and these wavelengths are key wavelengths for non-destructive Brix determination.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1123-1123
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• 2001

In recent years, a miniature spectrometer has been extensively developed due to the marriage of fiber optics and semiconductor detector array. This type of miniature spectrometer has advantages of low price and robustness due to the capability of mass production and no moving parts are required such as lenses, mirrors and scanning monochromator. These systems are ideal for use in teaching labs, process monitoring and field analyses. A portable near infrared (NIR) system has been developed for qualitative and quantitative analysis. This system includes a tungsten halogen lamp for light source, a fiber optics connected a light source, and a sample module to the microspectrometer, The size of spectrometer can be as small as 2.5 cm x 1.5 cm x 0.1 cm. Wavelength ranges can be chosen as 360-800 nm, 800-1100 nm and 1100-1900 nm depending on the type of detector. The software consists of various tools for multivariate analysis and pattern recognition techniques. To evaluate the system, long and short-term stability, wavelength accuracy, and stray light have been investigated and compared with conventional scanning type NIR spectrometer. This developed system can be sufficiently used for quantitative and qualitative analysis for various samples such as agricultural product, herbal medicine, food, petroleum, and pharmaceuticals, etc.