• Title/Summary/Keyword: Near-infrared Camera

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Analysis for Concentration Range of Fluorescein Sodium (플루오레신나트륨의 농도 범위 분석)

  • Lee, Da-Ae;Kim, Yong-Jae;Yoon, Ki-Cheol;Kim, Kwang-Gi
    • Journal of Biomedical Engineering Research
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    • v.41 no.2
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    • pp.67-74
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    • 2020
  • Brain tumors or gliomas are fatal cancer species with high recurrence rates due to their strong invasiveness. Therefore, the goal of surgery is complete tumor resection. However, the surgery is difficult to distinguish the border because tumors and blood vessels have the same color tone and shape. The fluorescein sodium is used as a fluorescence contrast agent for boundary separation. When the external light source is irradiated, yellow fluorescence is expressed in the tumor, which helps distinguish between blood vessels and tumor boundaries. But, the fluorescence expression of fluorescence sodium depends on the concentration of fluorescein sodium and such analytical data is insufficient. The unclear fluorescence can obscure the boundaries between blood vessels and tumors. In addition, reduce the efficiency of fluorescence sodium use. This paper proposes a protocol of concentration range for fluorescence expression conditions. Fluorescent expression was observed using a near-infrared (NIR) color camera with corresponding dilution using normal saline in 1 ml microtube. The flunoresence emission density range is 1.00 mM to 0.15 mM. The fluorescence emission begin to 1.00 mM and the 0.15 mM discolor. The discolor is difficult to fluorescence emission condition obserbation. Thus, the maximum density range of the bright fluoresecein is 0.15 mM to 0.30 mM. When the concentration range of fluorescein sodium is analyzed based on the gradient of fluorescence expression and the power measurement, the brightest fluorescence is expected to facilitate the complete resection of the tumor. For the concentration range protocol, setting concentration ranges and analyzing fluorescence expression image according to saturation and brightness to find optimal fluorescence concentration are important. Concentration range protocols for fluorescence expression conditions can be used to find optimal concentrations of substances whose expression pattern varies with concentration ranges. This study is expected to be helpful in the boundary classification and resection of brain tumors and glioma.

Comparative Analysis of Rice Lodging Area Using a UAV-based Multispectral Imagery (무인기 기반 다중분광 영상을 이용한 벼 쓰러짐 영역의 특성 분석)

  • Moon, Hyun-Dong;Ryu, Jae-Hyun;Na, Sang-il;Jang, Seon Woong;Sin, Seo-ho;Cho, Jaeil
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.917-926
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    • 2021
  • Lodging rice is one of critical agro-meteorological disasters. In this study, the UAV-based multispectral imageries before and after rice lodging in rice paddy field of Jeollanamdo agricultural research and extension servicesin 2020 was analyzed. The UAV imagery on 14th Aug. includesthe paddy rice without any damage. However, 4th and 19th Sep. showed the area of rice lodging. Multispectral camera of 10 bands from 444 nm to 842 nm was used. At the area of restoration work against lodging rice, the reflectance from 531 nm to 842 nm were decreased in comparison to un-lodging rice. At the area of lodging rice, the reflectance of around 668 nm had small increases. Further, the blue and NIR (Near-Infrared) wavelength had larger. However, according to the types of lodging, the change of reflectance was different. The NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red Edge) shows dome sensitivities to lodging rice, but they were different to types of lodging. These results will be useful to make algorithm to detect the area of lodging rice using a UAV.

Integrating UAV Remote Sensing with GIS for Predicting Rice Grain Protein

  • Sarkar, Tapash Kumar;Ryu, Chan-Seok;Kang, Ye-Seong;Kim, Seong-Heon;Jeon, Sae-Rom;Jang, Si-Hyeong;Park, Jun-Woo;Kim, Suk-Gu;Kim, Hyun-Jin
    • Journal of Biosystems Engineering
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    • v.43 no.2
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    • pp.148-159
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    • 2018
  • Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

Drone-based Vegetation Index Analysis Considering Vegetation Vitality (식생 활력도를 고려한 드론 기반의 식생지수 분석)

  • CHO, Sang-Ho;LEE, Geun-Sang;HWANG, Jee-Wook
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.2
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    • pp.21-35
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    • 2020
  • Vegetation information is a very important factor used in various fields such as urban planning, landscaping, water resources, and the environment. Vegetation varies according to canopy density or chlorophyll content, but vegetation vitality is not considered when classifying vegetation areas in previous studies. In this study, in order to satisfy various applied studies, a study was conducted to set a threshold value of vegetation index considering vegetation vitality. First, an eBee fixed-wing drone was equipped with a multi-spectral camera to construct optical and near-infrared orthomosaic images. Then, GIS calculation was performed for each orthomosaic image to calculate the NDVI, GNDVI, SAVI, and MSAVI vegetation index. In addition, the vegetation position of the target site was investigated through VRS survey, and the accuracy of each vegetation index was evaluated using vegetation vitality. As a result, the scenario in which the vegetation vitality point was selected as the vegetation area was higher in the classification accuracy of the vegetation index than the scenario in which the vegetation vitality point was slightly insufficient. In addition, the Kappa coefficient for each vegetation index calculated by overlapping with each site survey point was used to select the best threshold value of vegetation index for classifying vegetation by scenario. Therefore, the evaluation of vegetation index accuracy considering the vegetation vitality suggested in this study is expected to provide useful information for decision-making support in various business fields such as city planning in the future.

A Study on the Spectral Information and Reflectance Characteristic of Levee Crack (제방 균열의 분광정보 및 반사율 특성에 관한 연구)

  • Kim, Jong-Tae;Lee, Chang-Hun;Kang, Joon-Gu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.9
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    • pp.17-24
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    • 2020
  • This study examined the spectral information and reflectance of cracks of an embankment with drone-based hyperspectral imagery for crack detection. A Nano-Hyperspec mounted on a drone was used as a sensor, and hyperspectral videos of different intensities of illumination of the cracks on the embankment located in the downstream of Andong-Dam were obtained. An analysis of the data value of the illumination and peak data-value, the coefficients of determination were calculated to be 0.9864 of the uncracked areas and 0.9851 of the cracked area. The reflectance of each area showed a similar value and pattern, regardless of the intensity of illumination. This result may have occurred because the reference values of the white reference as the calculation criteria of reflectance varied according to the intensity of illumination. The reflectance at the cracked area was 5.65% lower in visible light and 4.58% lower in near-infrared light than that at the uncracked area. The detection of cracks may offer more precise results in further studies when the gimbal direction and camera angles of the drone are calibrated. Because hyperspectral imagery enables the detection of crack depths and types of clay minerals, which are difficult to identify in general RGB imagery, it can serve as a preemptive measure for evaluating the embankment stability.

Study of a Brain Tumor and Blood Vessel Detection System Using Multiple Fluorescence Imaging by a Surgical Microscope (수술현미경에서의 다중형광영상을 이용한 뇌종양과 혈관영상 검출 시스템 연구)

  • Lee, Hyun Min;Kim, Hong Rae;Yoon, Woong Bae;Kim, Young Jae;Kim, Kwang Gi;Kim, Seok Ki;Yoo, Heon;Lee, Seung Hoon;Shin, Min Sun;Kwon, Ki Chul
    • Korean Journal of Optics and Photonics
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    • v.26 no.1
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    • pp.23-29
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    • 2015
  • In this paper, we propose a microscope system for detecting both a tumor and blood vessels in brain tumor surgery as fluorescence images by using multiple light sources and a beam-splitter module. The proposed method displays fluorescent images of the tumor and blood vessels on the same display device and also provides accurate information about them to the operator. To acquire a fluorescence image, we utilized 5-ALA (5-aminolevulinic acid) for the tumor and ICG (Indocyanine green) for blood vessels, and we used a beam-splitter module combined with a microscope for simultaneous detection of both. The beam-splitter module showed the best performance at 600 nm for 5-ALA and above 800 nm for ICG. The beam-splitter is flexible to enable diverse objective setups and designed to mount a filter easily, so beam-splitter and filter can be changed as needed, and other fluorescent dyes besides 5-ALA and ICG are available. The fluorescent images of the tumor and the blood vessels can be displayed on the same monitor through the beam-splitter module with a CCD camera. For ICG, a CCD that can detect the near-infrared region is needed. This system provides the acquired fluorescent image to an operator in real time, matching it to the original image through a similarity transform.

A Study on the Comparison of Detected Vein Images by NIR LED Quantity of Vein Detector (정맥검출기의 NIR LED 수량에 따른 검출된 정맥 이미지 비교에 관한 연구)

  • Jae-Hyun, Jo;Jin-Hyoung, Jeong;Seung-Hun, Kim;Sang-Sik, Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.6
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    • pp.485-491
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    • 2022
  • Intravenous injection is the most frequent invasive treatment for inpatients and is widely used for parenteral nutrition administration and blood products, and more than 1 billion procedures are used for peripheral catheter insertion, blood collection, and other IV therapy per year. Intravenous injection is one of the difficult procedures to be performed only by trained nurses with intravenous injection training, and failure can lead to thrombosis and hematoma or nerve damage to the vein. Accordingly, studies on auxiliary equipment capable of visualizing the vein structure of the back of the hand or arm are being published to reduce errors during intravenous injection. This study is a study on the performance difference according to the number of LEDs irradiating the 850nm wavelength band on a vein detector that visualizes the vein during intravenous injection. Four LED PCBs were produced by attaching NIR filters to CCD and CMOS camera lenses irradiated on the skin to acquire images, sharpen the acquired images using image processing algorithms, and project the sharpened images onto the skin. After that, each PCB was attached to the front end of the vein detector to detect the vein image and create a performance comparison questionnaire based on the vein image obtained for performance evaluation. The survey was conducted on 20 nurses working at K Hospital.

Changes in the Hyperspectral Characteristics of Wheat Plants According to N Top-dressing Rates at Various Growth Stages (밀에서 질소 시비 조건에 따른 생육 단계별 초분광 특성 변화)

  • Jung, Jae Gyeong;Lee, Yeong Hun;Choi, Jae Eun;Song, Gi Eun;Ko, Jong Han;Lee, Kyung Do;Shim, Sang In
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.65 no.4
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    • pp.377-385
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    • 2020
  • Recently, wheat consumption has been increasing in Korea, requiring increased production. Nitrogen fertilization is a critical determinant in crop yield; therefore, it is necessary to optimize the nitrogen fertilization regime with current trends that emphasize the minimum impact of nitrogen fertilizer on the environment. In this study, both nondestructive spectral analysis using a hyperspectral camera and growth analysis were performed to determine the optimal N top-dressing rates after heading. The nitrogen application regimes consisted of three conditions according to the secondary top-dressing rate: N4:3:0 (0 kg 10 a-1), N4:3:3 (2.73 kg 10 a-1), and N4:3:6 (5.46 kg 10 a-1). Subsequently, growth and physiological investigations were performed at the jointing, heading, and ripening stages of wheat, and spectral investigations were conducted. On April 29, as the nitrogen fertilization rate was increased to N4:3:3 and N4:3:6, plant height and grain yield increased by 4% and 8%, and 8% and 52%, respectively, compared to those under N4:3:0. Leaf area index and SPAD value also increased by 13% and 24%, and 32% and 43%, respectively. The R (red), G (green), and B (blue) of leaf color were lowered by 15, 11, and 4 in N4:3:3 and 44, 34, and 18 in N4:3:6, respectively, as compared to the control. Grain yield was the highest at high top-dressing (N4:3:6), however, there was no difference between no top-dressing (N4:3:0) and intermediat top-dressing (N4:3:3). The reflectance analyzed using a hyperspectral camera showed a difference in the near-infrared (NIR) region on March 19, and on April 29, there was a difference both in the visible light region greater than 550 nm and the NIR region. Vegetation indices differed according to fertilization regime, except for the greenness index (GI). The results of this study showed that not only growth and physiological analysis but also spectral indices can be used to optimize the nitrogen top-dressing rate.

Direct Bonding of Si(100)/NiSi/Si(100) Wafer Pairs Using Nickel Silicides with Silicidation Temperature (열처리 온도에 따른 니켈실리사이드 실리콘 기판쌍의 직접접합)

  • Song, O-Seong;An, Yeong-Suk;Lee, Yeong-Min;Yang, Cheol-Ung
    • Korean Journal of Materials Research
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    • v.11 no.7
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    • pp.556-561
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    • 2001
  • We prepared a new a SOS(silicon-on-silicide) wafer pair which is consisted of Si(100)/1000$\AA$-NiSi Si (100) layers. SOS can be employed in MEMS(micro- electronic-mechanical system) application due to low resistance of the NiSi layer. A thermally evaporated $1000\AA$-thick Ni/Si wafer and a clean Si wafer were pre-mated in the class 100 clean room, then annealed at $300~900^{\circ}C$ for 15hrs to induce silicidation reaction. SOS wafer pairs were investigated by a IR camera to measure bonded area and probed by a SEM(scanning electron microscope) and TEM(transmission electron microscope) to observe cross-sectional view of Si/NiSi. IR camera observation showed that the annealed SOS wafer pairs have over 52% bonded area in all temperature region except silicidation phase transition temperature. By probing cross-sectional view with SEM of magnification of 30,000, we found that $1000\AA$-thick uniform NiSi layer was formed at the center area of bonded wafers without void defects. However we observed debonded area at the edge area of wafers. Through TEM observation, we found that $10-20\AA$ thick amourphous layer formed between Si surface and NiSix near the counter part of SOS. This layer may be an oxide layer and lead to degradation of bonding. At the edge area of wafers, that amorphous layer was formed even to thickness of $1500\AA$ during annealing. Therefore, to increase bonding area of Si NiSi ∥ Si wafer pairs, we may lessen the amorphous layers.

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Response of Structural, Biochemical, and Physiological Vegetation Indices Measured from Field-Spectrometer and Multi-Spectral Camera Under Crop Stress Caused by Herbicide (마늘의 제초제 약해에 대한 구조적, 생화학적, 생리적 계열 식생지수 반응: 지상분광계 및 다중분광카메라를 활용하여)

  • Ryu, Jae-Hyun;Moon, Hyun-Dong;Cho, Jaeil;Lee, Kyung-do;Ahn, Ho-yong;So, Kyu-ho;Na, Sang-il
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1559-1572
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    • 2021
  • The response of vegetation under the crop stress condition was evaluated using structural, biochemical, and physiological vegetation indices based on unmanned aerial vehicle (UAV) images and field-spectrometer data. A high concentration of herbicide was sprayed at the different growth stages of garlic to process crop stress, the above ground dry matter of garlic at experimental area (EA) decreased about 46.2~84.5% compared to that at control area. The structural vegetation indices clearly responded to these crop damages. Spectral reflectance at near-infrared wavelength consistently decreased at EA. Most biochemical vegetation indices reflected the crop stress conditions, but the meaning of physiological vegetation indices is not clear due to the effect of vinyl mulching. The difference of the decreasing ratio of vegetation indices after the herbicide spray was 2.3% averagely in the case of structural vegetation indices and 1.3~4.1% in the case of normalization-based vegetation indices. These results meant that appropriate vegetation indices should be utilized depending on the types of crop stress and the cultivation environment and the normalization-based vegetation indices measured from the different spatial scale has the minimized difference.