• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.839-842
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• 2009

It is used to differential image for moving object detection in general. But it is difficult to detect the accurate detection which uses differential image between frames. In this paper, the proposed method overcome the noise that is generated by camera, grabber card, or weather condition. It extract to moving big object such as human or vehicle. The proposed method process morphological filtering and binary for the image with noise, reduce error. We are expect to apply to a real-time moving object detection system at fog condition, pass the limit of the object detection method using the differential image.

• Analytical Science and Technology
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• v.16 no.2
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• pp.125-133
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• 2003

In order to determine the contents of trans-resveratrol in red wine, which was mainly consumed in Korea, both LC/MS-ESI and LC/MS-APCI methods were used after solid-phase (Sep-Pak $C_{18}$-cartridges) extraction. The contents of trans-resveratrol obtained by LC/MS-ESI were detected in the range of $0.06-4.31{\mu}g/mL$. The recoveries were ranged from 88.4 to 97.9%. The values of relative standard deviation were ranged from 0.6 to 4.6% and the detection limit was $0.001{\mu}g/mL$. The contents of trans-resveratrol obtained by LC/MS-APCI were detected in the range of $0.09-4.02{\mu}g/mL$ and the detection limit was $0.005{\mu}g/mL$.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.121-123
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• 2009

In previous research results, human error can be detected by using observation theory which assumed with step human failures, thus the detector has a limit to detect the human failures. In this paper, we propose a human error detect filter for given human failures. Various kind of human failures can be modeled, and from these models, an argumented human failure model can constructed. By using the argumented human failure model, the human error detect filter can be designed.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.215-218
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• 2002

영상 내에 존재하는 객체를 배경에서 분리해내는 영상분할에 대한 연구는 일반적으로 픽셀중심, 에지기반, 영역기반 그리고 모델기반의 영역에서 이루어져왔다. Active Contour 모델은 객체를 영상에서 분리하는 에지기반의 영상분할 방식이다. 전통적인 의미의 Active Contour 모델에서 사용한 그라디언트 함수 기반의 영상추출은 잡영이 많고 객체와 배경간 뚜렷한 경계가 없는 객체를 검출하는데는 그 한계를 보이고 있다. 이런 한계를 극복하고자 제안된 방법이 Mumford-Shah equation과 Lipshitz 함수를 이용한 Chan과 Vese의 Active Contour Model이다. 그런데 이 모델은 잡영이 많고 경계선이 뚜렷하지 않은 영상을 분할하는데는 효과적이나, 불균형적 조명이 있는 영상에서 객체를 분리해 내는데는 한계를 보이고 있다. 본 논문은 이러한 단점을 극복하기 위해 불균형적인 영상을 균일화하는 방법을 Chan과 Vese의 Active Contour 방식을 적용하기 전에 적용 시켜 영상 내 객체를 보다 효과적으로 추출하는 방법을 제안한다.

• Journal of Food Hygiene and Safety
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• v.8 no.3
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• pp.147-150
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• 1993

A novel rapid and sensitive method to detennine residual oxolinic acid in Acetes japonicus was developed. The residual oxolinic acid was extracted with ethylacetate and diluted oxalic acid, and interfering substances were removed by hexane. Fifty ppb residual concentration in the extract could be quantitated by UV-HPLC and the recovery rates were 79-91% according to the fortified amounts.

• Journal of Life Science
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• v.31 no.1
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• pp.10-16
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• 2021

The consumption of fresh-cut agricultural materials is increasing due to increased public interest in health and the increase of single-person households. Most fresh-cut agricultural materials can be eaten without heating, thus easily exposing the consumer to food-borne pathogens. As a result, food-borne diseases are increasing worldwide. In the analysis of food-borne pathogens, it is important to detect the strains, but this is time consuming and laborious. Alternative detection methods that have been introduced, include polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE), which is performed without prior culturing. Samples of fresh-cut agricultural materials, such as vegetables, were analyzed by the culture-based method. In 129 samples, non-pathogenic Escherichia coli (3.9%), Bacillus cereus (31.8%), Clostridium perfringens (5.4%), Yersinia enterocolitica (0.8%), and enterohemorrhagic E. coli (0.8%) were detected. Eight samples contaminated with bacteria were randomly selected, further analyzed by PCR-DGGE, and compared with the culture-based method. Two cases detected non-pathogenic E. coli by PCR-DGGE only, despite a lack of detection by the culture method. It was supposed there was possibility of sample loss during its 10-fold dilution for appropriate cultivation. In the detection of high-risk food-borne pathogens, it was found that the detection limit was lower in PCR-DGGE than in the culture-based method (10 CFU/g). This suggests that PCR-DGGE can be alternatively used to detect strains. On the other hand, low-risk food-borne pathogens seem to have higher detection limits in PCR-DGGE. Consequentially, this study contributes to the improvement of food-borne pathogen detection and the prevention of its related-diseases in fresh-cut agricultural materials.

• Food Science and Preservation
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• v.15 no.1
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• pp.88-93
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• 2008

This paper focused on the detection of the genetically modified soybean (Glycine max L. MERRILL) samples to search for the speedy analysis methods. We have identified the PCR (polymerase chain reaction) assay with a newly developed technique called DHPLC (denaturing high performance liquid chromatography) to screen the GMO in soybean. The DHPLC is i1s ability to directly detection specific sequences of DNA by using column. With these characteristics. the DHPLC assay had the advantage of simplicity, rapidty could obtain result within 20 minutes. Whereas $15{\times}10^{-4}ng/{\mu}L$ concentration could be detected with the PCR analysis, $15{\times}10^{-5}ng/{\mu}L$ concentration could be detected with the DHPLC method. Therefore, DHPLC method was considered to be a simple, fast and sensitivity screening method rather than PCR analysis for GMO detection in soybean.

• Journal of fish pathology
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• v.9 no.2
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• pp.169-176
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• 1996

An indirect double antibody enzyme-linked immunosorbent assay (ELISA) was developed for rapid detection of a new virus isolated from abnormally swimming salmonid fish, RVS (Retrovirus of salmonid). Results using brain tissue homogenates, and infected cell cultures are described. The sensitivity of the methods is $10^{2.6}$ $TCID_{50}/100{\mu}l$ of the examined cell culture fluid. The specificity was confirmed by the ELISA inhibition test and virological examinations. Viral antigen could be detected in artificially infected fish tissue homogenates. The assay will allow the diagnosis of RVS-infected fish within a day.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.463-465
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• 2021

Currently, the inspection method printed on food packages and boxes is to sample only a few products and inspect them with human eyes. Such a sampling inspection has the limitation that only a small number of products can be inspected. Therefore, accurate inspection using a camera is required. This paper proposes a deep learning object recognition technology model, which is an artificial intelligence technology, as a method for detecting the defects of expiration date printed on the product packaging. Using the Faster R-CNN (region convolution neural network) model, the color images, converted gray images, and converted binary images of the printed expiration date are trained and then tested, and each detection rates are compared. The detection performance of expiration date printed on the package by the proposed method showed the same detection performance as that of conventional vision-based inspection system.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.331-333
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• 2006

다양한 환경을 포항하고 있는 동영상에서 움직이는 객체를 추출, 인식하기 위해서는 배경 모델링이 중요하다. 기존의 대표적인 배경 모델링 방법으로 통계적 방법을 이용한 $W^4$ 방법이 있지만 칼라 영상의 다양한 환경에서 한계를 보인다. 본 논문은 큐 기반 배경 모델링을 이용한다. 이때 주요한 환경 변수가 되는 슬라이딩 윈도우의 큐 크기와 RGB 값의 그룹핑 크기, 프레임의 갱신검사 주기를 적응적으로 결정하기 위한 방법을 제안한다. 환경 변수를 결정하기 위친 객체 검출율, 객체 오검출율, 갱신율을 평가 기준으로 삼는다. 제안된 방법으로 실시간 처리에 부적합한 기존의 영상 처리 기법들을 개선하여 보다 효과적으로 객체를 인식할 수 있다.