• Preventive Nutrition and Food Science
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• 제10권1호
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• pp.29-33
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• 2005

To facilitate establishing regulations for irradiated foods, Korean traditional soybean-based fermented powdered doenjang (PD), kanjang (PK), kochujang (PKC) and chungkukjang (PC) were irradiated at 1, 3, 5 and 7 kGy, and subjected to irradiation detection analyses as part of establishing a database for detecting irradiated foods. Photostimulated luminescence (PSL) and electron spin resonance (ESR) were applied as the detection methods. Using PSL analysis, the irradiated PD, PK and PKC could be easily distinguished from the non-irradiated ones, while irradiation of the PC at 5 kGy or higher was detectable. The ESR spectra of the irradiated PD, PK and PKC exhibited symmetrical multiplet lines, which might be induced from the crystalline sugar, whereas, the PC showed a single signal at the paramagnetic centers. The signal intensity increased with incremental increases of irradiation doses distinguishing the irradiated samples from the control. In addition, the peak height also revealed that irradiation induced an increment in the intensity of single and/or multiplet lines of the ESR signals, resulting in clear confirmation of irradiation. Thus, the data from this study could be used as references for detecting irradiated soybean-based fermented powdered sauces.

• 한국해양환경ㆍ에너지학회지
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• 제15권4호
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• pp.323-329
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• 2012

본 연구에서는 분리된 기름-물 혼합물에 대해 단일 파장대역의 LED 광원으로 부터 흡수된 빛이 전자결합소자(CCD)에 투영된 영상을 분석하는 방법을 통해, 물 위에 기름의 존재 유 무와 상태를 파악할 수 있는 광학적 기름 탐지 방법에 대한 연구 결과를 제시한다. 물위에 기름의 존재 유 무와 기름의 두께 정보를 얻기 위해서, 혼합물을 통과하면서 감소되는 빛의 강도를 전자결합소자로 획득한 영상을 통해 빛의 세기를 분석하는 방법을 이용하였으며, 최고의 선택도를 가진 광원의 파장대역을 찾기 위해서 발광다이오드(LED)의 파장대역별로 선택도를 비교하는 실험을 진행하였다. 본 연구에서 사용된 발광다이오드 중 465 nm의 파장대역을 갖는 발광다이오드가 물과 기름의 존재유무 및 기름의 두께에 따라 감소되는 차이가 가장 크다는 결과를 얻을 수 있었다. 또한 실제 해상조건에서의 탐지 가능성을 확인하기 위해 밝기 조건과 수표면의 기울기 조건을 변화하는 실험을 수행하여 제안된 탐지 방법의 적용가능성을 확인하였다. 해당 연구를 통해서 해상에 유출된 기름을 물과 기름이 갖는 특정파장대역의 빛에 대한 흡수도의 차이로 탐지할 수 있는 새로운 광학적 분석 방법론을 제안한다.

• 한국컴퓨터정보학회논문지
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• 제10권6호
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• pp.1-8
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• 2005

얼굴 분석은 얼굴 인식 머리 움직임과 얼굴 표정을 이용한 인간과 컴퓨터사이의 인터페이스, 모델 기반 코딩, 가상현실 등 많은 응용 분야에서 유용하게 활용된다. 이러한 응용 분야에서는 얼굴의 특징점들을 정확하게 추출해야 한다. 본 논문에서는 눈, 눈썹, 입술의 코너와 같은 얼굴 특징을 자동으로 추출하는 방법을 제안한다. 먼저, 입력 영상으로부터 AdaBoost 기반의 객체 검출 기법을 이용하여 얼굴 영역을 추출한다. 그 다음에는 계곡 에너지. 명도 에너지, 경계선 에너지의 세 가지 특징 에너지를 계산하여 결합한다. 구해진 특징 에너지 영상에 대하여 에너지 값이 큰 수평 방향향의 사각형을 탐색함으로써 특징 영역을 검출한다. 마지막으로 특징 영역의 가장자리 부분에서 코너 검출 알고리즘을 적용함으로써 눈, 눈썹, 입술의 코너를 검출한다. 본 논문에서 제안된 얼굴 특징 추출 방법은 세 가지의 특징 에너지를 결합하여 사용하고 계곡 에너지와 명도 에너지의 계산이 조명 변화에 적응적인 특성을 갖도록 함으로써, 다양한 환경 조건하에서 견고하게 얼굴 특징을 추출할 수 있다.

• 대한전자공학회논문지SP
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• 제45권5호
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• pp.25-34
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• 2008

동일한 위치에서 같은 장면을 담고 있지만 서로 다른 시간에 획득된 두 장의 영상을 서로 비교하여 움직이는 자동차등에 의한 겹침과 같은 이상점의 집합을 검출할 수 있다. 영상들의 서로 다른 밝기 특성에 의한 영향을 줄이기 위하여 다항식 회귀 모델에 근거한 밝기 보정을 하였다. 이상점 집합으로 인한 영향을 약화시키면서 정확한 이상점 검출을 위하여 회귀분석을 단순히 반복하는 알고리듬을 도입하였다. 본 논문에서는 회귀분석을 반복하는 알고리듬의 성능을 잡음분산의 추정의 수렴 특성을 관찰하므로 분석하였으며, 교정 상수를 잡음분산 추정에 사용하여 강인한 검출이 가능하도록 하였다. 합성 영상과 실제 영상에 검출 알고리듬을 실험하여 그 강인성을 보였다.

• 한국입자에어로졸학회지
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• 제13권1호
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• pp.25-31
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• 2017

This paper offer the characteristics for the detection and classification of biological and non-biological aerosol particles in the air by using laser-induced-fluorescence (LIF) based Bio-aerosol Detection System (BDS). The BDS is mainly consist of an optical chamber, in-outlet nozzle system, 405 nm diode laser, an avalanche photo detector (APD) for scattering signal and photomultiplier tubes (PMT) for fluorescence signals in two different wavelength range ; F1, 510-600 nm and F2, 435-470 nm. The detection characteristics, especially ratio of fluorescence signal intensity were examined using well-known components : polystylene latex (PSL), fluorescence PSL, $2{\mu}m$ of SiO2 micro sphere, dried yeast, NADH, ovalbumin, fungicide powder and standard dust. The results indicated that the 405 nm diode laser-based LIF instrument can be a useful bio-aerosol detection system for unexpected biological threaten alter in real-time to apply for dual-use technology in military and civilian fields.

• Journal of Microbiology and Biotechnology
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• 제16권8호
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• pp.1169-1173
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• 2006

Imaging ellipsometry (IE) for detection of binding of Escherichia coli O157:H7 (E. coli O157:H7) to an immunosensor is reported. A protein G layer, chemically bound to a self-assembled layer of 11-mercaptoundecanoic acid (11-MUA), was adopted for immobilization of monoclonal antibody against E. coli O157:H7 (Mab). The immobilization of antibody was investigated using surface plasmon resonance. To fabricate antibody spots on a gold surface, protein G solution was spotted onto the gold surface modified with an 11-MUA layer, followed by immobilizing Mab on the protein G spot. Ellipsometric images of the protein G spot, the Mab spot, and Mab spots with binding of E. coli O157:H7 in various concentrations were acquired using the IE system. The change of mean optical intensity of the Mab spots in the ellipsometric images indicated that the lowest detection limit was $10^3$CFU/ml for E. coli O157:H7. Thus, IE can be applied to an immunosensor for detection of E. coli O157:H7 as a detection method with the advantages of allowing label-free detection, high sensitivity, and operational simplicity.

• Journal of Microbiology and Biotechnology
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• 제9권2호
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• pp.184-190
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• 1999

The use of the polymerase chain reaction (PCR) method was described using two sets of primers based on the ceuN gene (JEJ 1 and JEJ 2) which encodes a protein involved in siderophore transport and 16S rRNA gene (pA and pB) for the sensitive and specific detection of enteropathogen Campylobacter jejuni. Six oligonucleotides were utilized in an amplification experiment and PCR products of predicted sizes were generated from whole cells and boiled cell lysates at the same intensity. Two sets of the primer pairs, JEJ and pAB, were specific enough for all C. jejuni strains tested for the direct use of whole cells without DNA extraction or lysis steps. In the PCR using the pAB primer pair, the detection limit, as determined by the ethidium bromide staining of the amplification products on agarose gels, was at the level of $10^1$ bacteria cells or less in both the pure culture and artificially inoculated milk and chicken enrichment samples, whereas the detection limit with the JEJ primer pair was relatively low, i.e. $10^3$ cells or more in the same PCR samples. The PCR method using either a primer JEJ or pAB was both repeatable and specific for the detection of C. jejuni in food. This method is simply completed within 4 h.

• 한국멀티미디어학회논문지
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• 제18권10호
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• pp.1197-1204
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• 2015

Smoke detection plays an important role for the early detection of fire. In this paper, we suggest a newly developed method that generated LBPV(Local Binary Pattern Variance)s as special feature vectors from RGB contrast images can be applied to detect smoke using SVM(Support Vector Machine). The proposed method rearranges mean value of the block from each R, G, B channel and its intensity of the mean value. Additionally, it generates RGB contrast image which indicates each RGB channel’s contrast via smoke’s achromatic color. Uniform LBPV, Rotation-Invariance LBPV, Rotation-Invariance Uniform LBPV are applied to RGB Contrast images so that it could generate feature vector from the form of LBP. It helps to distinguish between smoke and non smoke area through SVM. Experimental results show that true positive detection rate is similar but false positive detection rate has been improved, although the proposed method reduced numbers of feature vector in half comparing with the existing method with LBP and LBPV.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.192-198
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• 2020

The 3D point cloud is a key technology of object detection for virtual reality and augmented reality. In order to apply various areas of object detection, it is necessary to obtain 3D information and even color information more easily. In general, to generate a 3D point cloud, it is acquired using an expensive scanner device. However, 3D and characteristic information such as RGB and depth can be easily obtained in a mobile device. GNN (Graph Neural Network) can be used for object detection based on these characteristics. In this paper, we have generated RGB and RGBD by detecting basic information and characteristic information from the KITTI dataset, which is often used in 3D point cloud object detection. We have generated RGB-GNN with i-GNN, which is the most widely used LiDAR characteristic information, and color information characteristics that can be obtained from mobile devices. We compared and analyzed object detection accuracy using RGBD-GNN, which characterizes color and depth information.

• 센서학회지
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• 제14권6호
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• pp.430-437
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• 2005

In this paper, we proposed a biologically inspired light-adaptive edge detection circuit based on the human retina. A saturating resistive network was suggested for light adaptation and simulated by using HSPICE. The light adaptation mechanism of the edge detection circuit was quantitatively analyzed by using a simple model of the saturating resistive element. A light-adaptive capability of the edge detection circuit was confirmed by using the one-dimensional array of the 128 pixels with various levels of input light intensity. Experimental data of the saturating resistive element was compared with the simulated results. The entire capability of the edge detection circuit, implemented with the saturating resistive network, was investigated through the two-dimensional array of the $64{\times}64$ pixels