• Korean Journal of Legislative Studies
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• v.25 no.3
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• pp.5-31
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• 2019

In the process of changing the Korean electoral system, various terms such as representation, majority, minority, plurality, and proportionality are not used correctly, making normative judgment on its desirable electoral system difficult. This paper clarifies the concepts and terminology related to the electoral system in order to enable proper normative discussion. First, the misuse of the names of the electoral system is reviewed. This includes the majority representative system versus the minority representative system, the single-member constituency versus the multi-member constituency, the absolute majority system versus the relative majority system, and the majority representative system versus the proportional representative system. Next, the principles of representation, proportionality, democracy, direct ballot, and equal ballot are discussed to evaluate the decisions made by the Constitutional Court of Korea. In the current electoral system of the National Assembly, the equivalence between its constituency member and its proportional representation member is very low in terms of proportionality between votes received and seats allotted. Finally, the coherence between proportional representation and other political institutions is examined. Strengthening the proportionality of parliamentary elections alone does not necessarily increase the proportionality of the entire power structure.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.667-675
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• 2009

Image matching is widely applied in image application areas, such as remote sensing and GIS. In general, the initial set of matching points always includes outlier which affect the accuracy of image matching. The purpose of this paper is to develop a robust approach for outlier detection and removal in order to keep accuracy in image matching applications. In this paper we use three automatic outlier detection techniques of backward matching and affine transformation, and RANSAC(RANdom SAmple Consensus) algorithm. Moreover, we calculate overlapping apply and steps block-based processing for fast and efficient image matching in pre-processing steps. The suggested approach in this paper has been applied to real frame image pairs and the results have been analyzed in terms of the robustness and the efficiency.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1454-1464
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• 2013

In this paper, we propose a rapid rigid registration method for the fusion visualization of intra-operative 2D XA and pre-operative 3D CTA images. In this paper, we propose a global movement estimation based on a trilateration for the fast and robust initial registration. In addition, the principal axis of each image is generated and aligned, and the bounding box of the vascular shape is compared for more accurate initial registration. For the fine registration, two images are registered where the distance between two vascular structures is minimized by selective distance measure. In the experiment, we evaluate a speed, accuracy and robustness using five patients' data by comparing the previous registration method. Our proposed method shows that two volumes can be registered at optimal location rapidly, and robustly comparing with the previous method.

• Journal of KIISE
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• v.43 no.9
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• pp.1034-1042
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• 2016

Together with machine-learning frameworks, area-based imagery registration techniques can be easily applied to diverse types of image pairs without predefined features and feature descriptors. However, feature detectors are often used to quickly identify candidate image patch pairs, limiting the applicability of these registration techniques. In this paper, we propose a ConvNet (Convolutional Network) "Dart" that provides not only the matching metric between patches, but also information about their distance, which are helpful in reducing the search space of the corresponding patch pairs. In addition, we propose a ConvNet "Fad" to identify the patches that are difficult for Dart to improve the accuracy of registration. These two networks were successfully implemented using Deep Learning with the help of a number of training instances generated from a few registered image pairs, and were successfully applied to solve a simple image registration problem, suggesting that this line of research is promising.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.321-328
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• 2003

This Paper Proposes a size-variable block matching algorithm for motion vector extraction. The Proposed algorithm dynamically determines the search area and the size of a block. We exploit the constraint of small velocity changes of a block along the time to determine the origin of the search area. The range of the search area is adjusted according to the motion coherency of spatially neighboring blocks. The process of determining the sire of a block begins matching with a small block. If the matching degree is not good enough, we expand the size of a block a little bit and then repeat the matching process until our matching criterion Is satisfied. The experimental results show that the proposed algorithm can yield very accurate block motion vectors. Our algorithm outperforms other algorithms in terms of the estimated motion vectors, though our algorithm requires some computational overhead.

• Journal of KIISE:Software and Applications
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• v.32 no.1
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• pp.41-49
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• 2005

In this Paper, we Propose an automatic lung registration technique using local distance propagation for correcting the difference between two temporal images by a patient's movement in abdomen CT image obtained from the same patient to be taken at different time. The proposed method is composed of three steps. First, lung boundaries of two temporal volumes are extracted, and optimal bounding volumes including a lung are initially registered. Second, 3D distance map is generated from lung boundaries in the initially taken volume data by local distance propagation. Third, two images are registered where the distance between two surfaces is minimized by selective distance measure. In the experiment, we evaluate a speed and robustness using three patients' data by comparing chamfer-matching registration. Our proposed method shows that two volumes can be registered at optimal location rapidly. and robustly using selective distance measure on locally propagated 3D distance map.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.439-441
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• 2001

대용량 한글 문서를 대상으로 하는 검색 시스템은 고속의 단어 매칭 알고리즘을 필요로 한다. 이 논문은 두 단계 매칭 접근 방법을 제시하고 그 유용성을 실험을 통해 입증한다. 특징으로는 웨이브렛(wavelet) 계수를 사용하여 첫 단계에서는 적은 수의 특징만을 사용하여, 거친 정합(coarse matching)을 하며 두 번째 단계에서는 미세한 정합(fine matching)을 한다. 거친 정합은 가능성이 없는 단어를 아주 빠른 속도로 걸러내는 역할을 한다. 실제 한글 단어 영상 데이터베이스에 적용한 실험 결과 검색률의 희생 없이 약 7배의 속도 향상을 얻었다.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1
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• pp.31-38
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• 1998

본 논문에서는 애매성을 고려한 이론을 적용하여 유사도를 측정한 후 퍼지 관계 행 렬을 생성하여 인식을 행하는 방법을 제안하고자 한다. 인식 시스템은 모델과 입력 영상의 특징값을 정합하여 행하게 되는데 이때 얼마나 유사한가를 계산하는 유사도 측정은 대단히 중요한 작업중의 하나가 된다. 이를 위해 톨이론과 퍼지이론의 일치도 연산을 이용하여 유 사도를 측정하며, 퍼지 관계 행렬을 생성하여 정합을 행하고자 한다. 제안한 알고리즘에 대 해 3차원 물체와 얼굴 영상을 대상으로 실험을 수행하였으며 이를 통해 본 논문의 유용성을 입증하고자 한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.397-400
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• 2003

공장 현장에서 적용할 수 있는 산업용 비전 검사시스템의 개발을 위해서는 안정적이면서도 고속 패턴 정합이 가능한 알고리즘의 개발이 요구된다. 기존의 농담정규화상관(NGC)법을 사용하는 알고리즘은 과도한 계산량과 조명의 불안정에 영향을 많이 받는 문제점이 있다 본 논문에서는 영상 피라미드와 물체경계의 에지점들을 이용하여 기존 NGC 알고리즘의 단점을 보완하고 고속 패턴정합을 수행하는 에지기반 점상관 알고리즘을 제안하고 이를 실제 영상에 적용하여 그 신뢰성을 검증한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.587-589
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• 2019

템플릿 정합을 사용하는 영상인식 방법은 사용이 편리한 장점이 있지만, 템플릿과 정합 영상의 자세가 맞지 않으면 좋은 결과를 기대하기 어렵다. 이와 같은 단점을 보완하기 위해서 본 논문에서는 템플릿과 정합 영상 사이에 2 차원 방향과 크기에 차이기 있어도 성능이 유지될 수 있는 방안을 제시한다. 사용의 편의성을 고려하여, 템플릿 이외의 추가정보, 예를 들어 직교투영상의 거리 정보가 없어도 사용 가능하도록 알고리즘을 설계하는데 주력한다.