• Proceedings of the Korean Information Science Society Conference
• /
• 2003.04c
• /
• pp.289-291
• /
• 2003

3차원 형상 모델의 비교 연구는 의학, 분자 생물학, 컴퓨터 그래픽스 등의 분야에서 다루게 되는 기본적인 문제들 중의 하나이다. 본 논문에서는 3차원 형상 모델간의 유사성을 측정하기 위한 방법을 제안한다. 본 시스템은 삼각형 메쉬 모델을 유사성 평가에 사용한다. 유사성 비교를 위해 실루엣 영상을 이용하고, 유사 점도의 계산을 위한 측도(metric)로는 부피(Volume), 곡률(Curvature), 직선거리(Euclidean Distance)를 사용한다. 또한 다양한 방식에 의해 획득된 형상 모델의 비교를 위하여 먼저 포즈 정규화(Pose Normalization)를 한 후 유사성 평가 작업을 수행한다. 본 논문에서 제시한 3차원 형상 비교 시스템은 형상 비교대상들에 대한 전체 변형 및 부분 변형, 그리고 회전등에 강인함을 보였다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10b
• /
• pp.688-690
• /
• 2003

본 논문에서는 다해상도 2차원 실루엣 영상들을 이용하여 3차원 모델간의 형상 유사성을 비교하기 위한 방법을 제안한다. 제안 시스템은 포즈 정규화 모듈, 유사성 계산 모듈, 3차원 시각화 모듈로 구성된다. 형상 비교를 위해서 먼저, 3차원 인체 장기 모델을 입력으로 받아서 정규화를 수행하고, 다해상도 깊이맵을 획득한다. 이어서 유사성 비교를 위해 실루엣 영상을 추출한 후, 유사도 측정을 위해 시그니쳐를 측도로 사용한다. 최종적으로 계산된 결과들은 3차원 글리프 및 컬러 코딩을 이용하여 시각화된다. 본 논문에서 제시한 3차원 형상 비교 시스템은 전처리 단계에서의 정규화 수행을 통하여 스케일 및 회전 변환에 불변하는 특성을 보인다. 그리고 다양한 레벨의 깊이맵을 형상 비교에 사용하여 다해상도 기반의 유사성 평가를 지원하며, 평가 계산 속도와 정확성간의 유연성을 제공한다. 또한 3차원 히스토그램. 3차윈 글리프. 컬러 코딩 시각화 기법들과 2차원 실루엣 피킹 인터페이스를 통하여 인체 장기 모델간의 정량적 형상 차이를 사용자가 직관적으로 평가할 수 있도록 한다. 본 시스템은 차후 데이터베이스를 이용한 원격 진료 시스템에서의 질병 진단, 추적 관찰. 치료계획 등에 활용될 수 있을 것이다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.11a
• /
• pp.199-202
• /
• 2007

The similarity measure is constructed for non-convex fuzzy membership function using well known Hamming distance measure. Comparison with convex fuzzy membership function is carried out, furthermore characteristic analysis for non-convex function are also illustrated. Proposed similarity measure is proved and the usefulness is verified through example. In example, usefulness of proposed similarity is pointed out.

• Journal of KIISE
• /
• v.44 no.5
• /
• pp.553-558
• /
• 2017

With the rapid growth of Big Data, research on extracting meaningful information is being pursued by both academia and industry. Especially, data characteristics derived from analysis, and researcher intention are key factors for search algorithms to obtain accurate output. Therefore, reflecting both data characteristics and researcher intention properly is the final goal of data analysis research. The data analyzed properly can help users to increase loyalty to the service provided by company, and to utilize information more effectively and efficiently. In this paper, we explore various methods of document-evaluation, so that we can improve the accuracy of searching article one of the most frequently searches used in real life. We also analyze the experiment result, and suggest the proper manners to use various methods.

• The Korean Journal of Applied Statistics
• /
• v.26 no.1
• /
• pp.81-92
• /
• 2013

It is important to construct a firm basis for accusing potential violators of academic integrity in order to avoid spurious accusations and false convictions. Educational researchers have developed many statistical methods that can either uncover or confirm cases of cheating on tests. However, most of them rely on simple correlation-based measures, and often fail to account for patterns in responses or answers. In this paper, we propose a new statistical index denoted by a Standardized Signed Entropy Similarity Score to resolve this difficulty. In addition, we apply the proposed method to analyze a real data set and compare the results to other existing methods.

• The Korean Journal of Applied Statistics
• /
• v.30 no.4
• /
• pp.567-578
• /
• 2017

Grouped multivariate data can be tested for differences between two or more groups using multivariate analysis of variance (MANOVA). However, this method cannot be used if several assumptions of MANOVA are violated. In this case, multidimensional scaling (MDS) and analysis of distance (AOD) can be applied to grouped dissimilarities based on the various distances. A permutation test is a non-parametric method that can also be used to test differences between groups. MDS is used to calculate the coordinates of observations from dissimilarities and AOD is useful for finding group structure using the coordinates. In particular, AOD is mathematically associated with MANOVA if using the Euclidean distance when computing dissimilarities. In this paper, we study the between and within group structure by applying MDS and AOD to the grouped dissimilarities. In addition, we propose a new test statistic using the group structure for the permutation test. Finally, we investigate the relationship between AOD and MANOVA from dissimilarities based on the Euclidean distance.

• Journal of Digital Contents Society
• /
• v.9 no.1
• /
• pp.53-60
• /
• 2008

Based on similarities between fuzzy set theory and mathematical morphology, Grabish proposed a fuzzy morphology based on the Sugeno fuzzy integral. This paper proposes a fuzzy mathematical morphology based on the defuzzification of the fuzzy measure which corresponds to fuzzy integral. Its process makes a fuzzy set used as a measure of the inclusion of each fuzzy measure for subsets. To calculate such an integral a $\lambda$-fuzzy measure is defined which gives every subsets associated with the universe of discourse, a definite non-negative weight. Fast implementable definitions for erosion and dilation based on the fuzzy measure was given. An application for robust skeletonization of two-dimensional objects was presented. Simulation examples showed that the object reconstruction from their skeletal subsets that can be achieved by using the proposed was better than by using the binary mathematical morphology in most cases.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.11
• /
• pp.67-73
• /
• 2010

In this paper, a new face detection method that is more accurate than the conventional methods is proposed. This method utilizes a hybrid of Hausdorff distance based on the geometric similarity between the two sets of points and the LBP distance based on the distribution of local micro texture of an image. The parameters for normalization and the optimal blending factor of the two different metrics were calculated from training sample images. Popularly used face database was used to show that the proposed method is more effective and robust to the variation of the pose, illumination, and back ground than the methods based on the Hausdorff distance or LBP distance. In the particular case, the average error distance between the detected and the true face location was reduced to 47.9% of the result of LBP method, and 22.8% of the result of Hausdorff method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.3
• /
• pp.203-210
• /
• 2000

In this paper, we propose a new unsupervised learning network and competitive learning algorithm for pattern classification. The proposed network is based on relative similarity, which is similarity measure between input data and cluster group. So, the proposed network and algorithm is called relative similarity network(RSN) and learning algorithm. According to definition of similarity and learning rule, structure of RSN is designed and pseudo code of the algorithm is described. In general pattern classification, RSN, in spite of deletion of learning rate, resulted in the identical performance with those of WTA, and SOM. While, in the patterns with cluster groups of unclear boundary, or patterns with different density and various size of cluster groups, RSN produced more effective classification than those of other networks.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1998.05b
• /
• pp.746-751
• /
• 1998

붕소 중성자 포획 요법(BNCT, Boron Neutron Capture Therapy)용 열외중성자빔의 개발을 위하여 방사성 동위원소인 Cf-252를 중성자 선원으로 사용하였으며 상대적으로 낮은 중성자속을 높이기 위하여 미임계 증배 집합체를 이용하였다. 이전에 계시된 미임계 증배 집합체는 높은 핵연료 농축도를 필요로 하는 단점이 있어 본 연구에서는 이를 감소시키기 위한 몇 가지 설계안을 제시하였다. 중성자빔 설계를 위하여 몬테칼로 방법을 이용한 전산코드인 MCNP를 이용, 타원형두뇌 팬텀 내에서 AD, AR ADDR및 각각의 선량성분 등을 계산함으로써 설계된 중성자빔의 특성분석을 수행하였다. 새롭게 개선되어 제시된 중성자빔의 설계는 상대적으로 낮은 핵연료 농측도를 보이면서 기존의 결과와 유사한 결과를 보여주고 있으며 특히 두뇌 팬텀 내에서의 선량률은 기존에 비해 매우 높은 값을 보임으로써 짧은 시간에 효과적으로 뇌종양을 치료할 수 있는 이 점이 있다.