• 한국컴퓨터정보학회논문지
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• 제10권1호
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• pp.67-72
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• 2005

대부분의 이진화 알고리즘은 임계치를 결정하기 위하여 히스토그램을 사용하여 밝기 분포를 분석한다. 배경과 물체의 명도차이가 큰 경우에는 양봉 형태의 히스토그램이 나타나며 최적의 임계치를 찾기 위해 히스토그램 골짜기를 선택하는 것만으로도 양호한 임계치 결과를 얻을 수 있다. 반면에 배경과 물체의 밝기 차이가 크지 않거나 밝기 분포가 양봉 특성을 보이지 않을 때는 히스토그램 분석만으로 적절한 임계치를 얻기 어렵다 본 논문에서는 RGB 컬러 모형의 각 색상에 대하여 퍼지 소속 함수를 적용하고, 그 결과를 이용해 배경에 비해 가독성이 높은 특징들을 배경과 분리하는 방법을 제안한다. 제안된 이진화 방법은 RGB의 각 색상에 퍼지 소속 함수를 적용하여 얻은 값들을 이용해 이진화한다. 기존의 임계치를 이용한 이진화 방법에 비해 잡음 영역을 상당히 제거 할 수 있으며, 운송 컨테이너 영상에 적용한 결과, 기존의 방법에 비해 효율적인 것을 확인하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1994년도 추계학술대회
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• pp.43-46
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• 1994

A new spatial localization technique using high-order surface gradient coil (SGC) is proposed. Although the Spatial Selection with High-Order gradient (SHOT) can provide a 2-D selection with only one selective RF pulse, the high-order gradient produced by cylindrical-shape coils has not been clinically useful for clinical systems due to the large minimum selection size caused by the limited radial gradient intensity. However, by using the proposed high-order SGCs located near the imaging region, the size of volume selection can be reduced to a clinically useful 1-4 cm in diameter by applying stronger radial gradient with much less gradient driving power. A 40 cm-by-40 cm $r^{2}$ SGC has been designed and constructed, and phantom and volunteer studies have been performed. Experimental results using spatially localized MRI show good agreement to the theoretically predicted behavior.

• 한국통신학회논문지
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• 제21권3호
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• pp.553-563
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• 1996

Detecting edges is one of issues with essentialimprotance in the area of image analysis. An edge in an image is a boundary or contour at which a significant change occurs in image intensity. Edge detection has been studied in many addlications such as imagesegmentation, robot vision, and image compression. In this paper, we propose an automatic threshold selection scheme for edge detection and show its application to noise elimination. The scheme suggested here applied statistical properties of the noise estimated from a noisy image to threshold selection. Since a selected threshold value in the scheme depends on not the characgreistic of an orginal image but the statistical feature of added noise, we can remove ad-hoc manners used for selecting the threshold value as well as decide the value theoretically. Furthermore, that shceme can reduce the number of edge pixels either generated or lost by noise. an application of the scheme to noise elimination is shown here. Noise in the input image can be eliminated with considering the direction of each edge pixedl on the edge map obtained by applying the threshold selection scheme proposed in this paper. Achieving significantly improved results in terms of SNR as well as subjective quality, we can claim that the suggested method works well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권1호
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• pp.240-259
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• 2020

Analyzing network traffic is the basis of dealing with network security issues. Most of the network security systems depend on the feature selection of network traffic data and the detection ability of malicious traffic in network can be improved by the correct method of feature selection. An FAFS method, which is short for Fuzzy Association Feature Selection method, is proposed in this paper for network malicious traffic detection. Association rules, which can reflect the relationship among different characteristic attributes of network traffic data, are mined by association analysis. The membership value of association rules are obtained by the calculation of fuzzy reasoning. The data features with the highest correlation intensity in network data sets are calculated by comparing the membership values in association rules. The dimension of data features are reduced and the detection ability of malicious traffic detection algorithm in network is improved by FAFS method. To verify the effect of malicious traffic feature selection by FAFS method, FAFS method is used to select data features of different dataset in this paper. Then, K-Nearest Neighbor algorithm, C4.5 Decision Tree algorithm and Naïve Bayes algorithm are used to test on the dataset above. Moreover, FAFS method is also compared with classical feature selection methods. The analysis of experimental results show that the precision and recall rate of malicious traffic detection in the network can be significantly improved by FAFS method, which provides a valuable reference for the establishment of network security system.

• Journal of Animal Science and Technology
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• 제55권6호
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• pp.501-508
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• 2013

This study was conducted to determine genetic correlations among carcass traits measured by ultrasound and real carcass measurements and to estimate indirect selection responses for real carcass traits based on ultrasound measurements in Hanwoo cows. To accomplish this, 22,080 ultrasound measurement records from 17,926 cows collected from 2001 to 2012 and 11,907 carcass records obtained from fattened cattle from 2008 to 2012 were used. Genetic parameters were estimated based on eye muscle area (EMA), backfat thickness (BF) and marbling score (MS) measured by ultrasound-scanning of live cows and using the official technique on chilled bovine half-carcasses after slaughtering. Heritability and genetic correlation for carcass traits were estimated using a mixed model equation that consisted of environmental effects as fixed parameters and additive genetic effects and residual effects as random parameters, assuming that traits were different between ultrasound and carcass measurements. This statistical method was applied to the average information restricted maximum likelihood method. The heritability of EMA, BF and MS measured by ultrasound were 0.33, 0.61 and 0.46, respectively, while the heritability estimates of the corresponding traits based on carcass measurements were 0.29, 0.40 and 0.38, respectively and the genetic correlation between ultrasound and carcass traits for EMA, BF and MS were 0.41, 0.78 and 0.67, respectively. The genetic correlation between ultrasound and carcass traits was highly positive. Additionally, the selection response for marbling score was estimated to be 0.42 per generation if the cows were selected based on the ultrasound scan marbling score with an assumed selection intensity of 0.8. Overall, these results indicate that the ultrasound scan technique would be applicable to judging cow selection for genetically improved meat quality.

• Journal of the Korean Wood Science and Technology
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• 제43권6호
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• pp.721-729
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• 2015

목재의 재질특성은 토양, 기후, 임분특성 등의 환경적 요인뿐만 아니라 인위적인 처리에 의해서도 바뀌게 되므로 남부지역의 전라남도 완도 수목원에서 무간벌, 약도간벌, 강도간벌의 간벌강도에 따른 목재의 조직 물리 역학적 특성을 평가 분석한 결과 간벌 강도에 따라 여러 조건에서 높은 상관관계를 나타내었다. 특히 간벌강도는 연륜폭과 역학적 특성에서 밀접한 상관관계를 나타내었다. 본 연구결과 붉가시나무의 간벌강도와 재질특성 사이에서 상관관계가 나타났고 이러한 결과는 목재를 시업체계와 육림방법 시스템에 적용할 수 있는 기초자료로서 활용가치가 높을 것으로 판단된다.

• 대한전자공학회논문지SP
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• 제42권2호
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• pp.37-48
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• 2005

본 논문에서는 적외선 영상에서 밝기변화를 예측하기 어려운 일정한 크기의 관심 물체를 검출하기 위하여, 밝기순위 특징과 이론 이용한 물체식별기법을 제안한다. 제안하는 밝기순위 특징은 밝기값의 분포가 균일하도록 영상을 정규화하여 나타낸 것으로, 적외선 영상과 같이 검출대상 물체의 밝기분포를 쉽게 예측하기 어려운 경우에 적합한 특징이다. 제안하는 식별기법은 주어진 후보영역이 검출대상 물체의 학습영상들에 대해 밝기순위가 부합하는 정도를 수치화하여 각각의 후보영역을 물체와 비물체로 식별한다 제안하는 기법을 통하여 별도의 후보영역 선정과정 없이도 일정한 크기의 관심 물체에 대해 화소단위의 검출결과를 획득할 수 있다. 실험에서는 적외선 자동차 영상을 이용하여 밝기순위특징이 적외선 영상 내 물체식별에 적합함을 보이고, 잡음 및 물체의 크기변화, 기울어짐이 존재하는 상황에서의 검출결과를 보인다.

• 수산해양기술연구
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• 제52권4호
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• pp.281-289
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• 2016

Spinyhead sculpin Dasycottus setiger, a species of cold water fish, is distributed along the eastern coastal waters of Korea. A series of fishing experiments was carried out in the waters near Uljin from June, 2002 to November, 2004, using the experimental monofilament gill nets of different mesh sizes (82.2, 89.4, 104.8, and 120.2 mm) to describe the selectivity of the gill net for the fish. The SELECT (Share Each Length's Catch Total) analysis with maximum likelihood method was applied to fit the different functional models (normal, lognormal, and bi-normal models) for selection curves to the catch data. The bi-normal model with the fixed relative fishing intensity was selected as the best-fit selection curve by AIC (Akaike's Information Criterion) comparison. For the best-fit selection curve, the optimum relative length (the ratio of fish total length to mesh size) with the maximum efficiency and the selection range ($R_{50%,large}-R_{50%,small}$) of 50% retention were obtained as 2.363 and 0.851, respectively. The ratios of body girth to mesh perimeter at 100% retention where the selection curve of each mesh size represented the optimum total length were calculated as the range of 0.86 ~ 0.87.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4513-4532
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• 2014

Motivated by the Weber's Law, this paper proposes an efficient and robust shape descriptor based on the perceptual stimulus model, called Weber's Law Shape Descriptor (WLSD). It is based on the theory that human perception of a pattern depends not only on the change of stimulus intensity, but also on the original stimulus intensity. Invariant to scale and rotation is the intrinsic properties of WLSD. As a global shape descriptor, WLSD has far lower computation complexity while is as discriminative as state-of-art shape descriptors. Experimental results demonstrate the strong capability of the proposed method in handling shape retrieval.

• Journal of the Korean Data and Information Science Society
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• 제10권1호
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• pp.119-133
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• 1999

마코브체인 몬테칼로 방법을 소프트웨어 신뢰모형에 이용하였다. 베이지안 추론에서 조건부 분포를 가지고 사후분포를 결정하는데 있어서의 계산 문제를 고찰하였다. 특히 레코드값을 통계량을 갖고서 혼합과정과 중첩과정에 대하여 깁스샘플링 알고리즘과 메트로폴리스 알고리즘을 활용하여 베이지안 계산과 모형 선택을 제시하고 모의실험자료를 이용하여 수치적 인 계산을 시행하고 그 결과를 비교하였다.