• Journal of Biosystems Engineering
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• v.26 no.2
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• pp.169-176
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• 2001

Defect of apple was depreciated the product value and causes storage disease seriously. To detect the defect of ‘Fuji’apple with machine vision system, the optical characteristics of defect should be investigated. In this research, absorbance spectra of defect were acquired by spectrophotometer in the range of visible and NIR region(400∼1,100nm) and L*a*b* color values were also acquired by colorimeter. NIR machine vision system was constructed with B&W camera, frame grabber, 16 tungsten-halogen lamps, variable focal length lens and NIR bandpass filter which was mounted to lens outward. Average gray values of defect at 15 NIR wavelength were acquired and the significant NIR wavelength was selected by comparing Mahalanobis distance between sound and defective apple. As the result of Mahalanobis distance analysis, the significant wavelength to discriminate the defectives in ‘Fuji’apple were found to be 720nm for scab and 970nm for bruise and cuts and 920nm was also effective regardless of defective types.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.1
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• pp.33-39
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• 2016

Color image dehazing techniques have been extensively studied, and especially the dark channel prior (DCP)-based method has been widely used. Near infrared (NIR) image based applications are also widespread; however, NIR image-specific dehazing techniques have not attracted great interest. In this paper, the characteristics of NIR images are analyzed and compared with the color images' characteristics. The conventional color image dehazing method is also applied to NIR images to understand its effectiveness on different frequency-band signals. Furthermore, we modify the DCP method considering the characteristics of NIR images and show that our proposed method results in improved dehazed NIR images.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.7
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• pp.1017-1025
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• 2000

The traditional methods for determining the quality of milk, cheese and meat are tedious and expensive, with a significant wastage of chemicals which pollute the environment. To overcome these disadvantages, the potential of near infrared spectrophotometry (NIR) for monitoring the quality of milk and meat has been evaluated by a number of researchers. While most studies indicate that NIR can be used to predict chemical composition of milk and meat, and to monitor the cutting-point during cheese manufacturing, one study demonstrated the potential of NIR to predict sensory characteristics (e.g. hardness and tenderness) of beef. These calibrations were developed on a small number of samples, limiting their value for adoption by the industries. Now that the sophisticated computer software is available, more robust calibrations need to be developed to monitor both chemical and physical characteristics of meat and meat products simultaneously.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.92-97
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• 2022

Plastics are classified into 7 types such as PET (PETE), HDPE, PVC, LDPE, PP, PS, and Other for separation and recycling. Recently, large corporations advocating ESG management are replacing them with bioplastics. Incineration and landfill of disposal of plastic waste are responsible for air pollution and destruction of the ecosystem. Because it is not easy to accurately classify plastic materials with the naked eye, automated system-based screening studies using various sensor technologies and AI-based software technologies have been conducted. In this paper, NIR scanning devices considering the NIR wavelength characteristics that appear differently for each plastic material and a system that can identify the type of plastic by learning the NIR spectrum data collected through it. The accuracy of plastic material identification was evaluated through a decision tree-based SVM model for multiclass classification on NIR spectral datasets for 8 types of plastic samples including biodegradable plastic.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.203-208
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• 2007

Drying characteristics are confirmed by experiment to a printing machine which use Gravure ink or metal ink for an optimum design of direct radiation drying system room using NIR. As a result, Drying is easily accomplished in short distance and low moving speed in Gravure ink, but drying is dropped in metal ink because of oil. This confirmed that the development of water metal ink had to be proceeded to accomplish a perfect drying condition.

• Journal of the Korean Solar Energy Society
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• v.24 no.1
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• pp.21-27
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• 2004

Near Infrared Ray (NIR) are primarily of interest to the high energy physicist. It is the intermediate portion of the spectrum, which extends from approximately 0.8 to 1.5 ${\mu}m$ and include a portion of the all of infrared, that is thermal radiation and is pertinent to heat transfer. It is important to study that temperature distribution of the drying materials by surface encompasses a range of NIR wave lengths. This study is to investigate the characteristics of NIR dryer by experimental results. it was made a comparison with various textiles, velocity ratio and distance of lamp and textiles. In case of spongy type textile the drying performance is the superior of all. The 0.15m distance drying effect of improvement 30% more than 0.26m distance between lamp and textiles. As the contained water increases, the drying speed for textile can be increased.

• Journal of the Microelectronics and Packaging Society
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• v.27 no.4
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• pp.107-111
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• 2020

Recently, as an aging society progresses, a lot of interest in health and diagnosis is increasing, As the field of various bio-imaging systems for guided surgery capable of accurate diagnosis has emerged as important, a Fluorescence imaging system capable of accurate measurement and real-time confirmation has emerged as an important field. Fluorescence images currently being used are mainly in the NIR-I band, but many studies are in progress in the NIR-II band in order to improve resolution and confirm fluorescence deeply and accurately. In this paper, the difference between NIR-I and NIR-II, optical characteristics, and SBR (signal to background ration) of a fluorescent imaging system, was investigated using the finite element (FEM) method. After confirming, it was confirmed that the SBR was 16.2 times higher in the NIR-II area than in the NIR-I by making the skin phantom and measuring the fluorescence. It is confirmed that the enhancement in SBR of the Fluorescence imaging system is more effective in the NIR-II region than in the NIR-I region and expected to be used in application fields such as guided surgery, bio-sensor and also device which can detect the defect of optical devices.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.12a
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• pp.340-345
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• 1999

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1997.12a
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• pp.362-367
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• 1997

• Clean Technology
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• v.18 no.1
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• pp.31-37
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• 2012

Biomass has become a major feedstock for bioenergy and other bio-based products because of its renewability and environmental benefits. Various researches have been done in the prediction of crucial characteristics of biomass, including the active utilization of spectroscopy data. Near infrared (NIR) spectroscopy has been widely used because of its attractive features: it's non-destructive and cost-effective producing fast and reliable analysis results. This work developed the multivariate statistical scheme for predicting weight loss profiles based on the utilization of NIR spectra data measured for six lignocellulosic biomass types. Wavelet analysis was used as a compression tool to suppress irrelevant noise and to select features or wavelengths that better explain NIR data. The developed scheme was demonstrated using real NIR data sets, in which different prediction models were evaluated in terms of prediction performance. In addition, the benefits of using right pretreatment of NIR spectra were also given. In our case, it turned out that compression of high-dimensional NIR spectra by wavelet and then PLS modeling yielded more reliable prediction results without handling full set of noisy data. This work showed that the developed scheme can be easily applied for rapid analysis of biomass.