• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.161-168
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• 2009

Recently, use of various position base servicesthat collect position information for moving object and utilize in real life is increasing by the development of wireless network technology. Accordingly, new index structures are required to efficiently retrieve the consecutive positions of moving objects. This paper addresses an improved trajectory split algorithm for the purpose of efficiently supporting spatio-temporal range queries using index structures that use Minimum Bounding Rectangles(MBR) as trajectory approximations. We consider volume of Extended Minimum Bounding Rectangles (EMBR) to be determined by average size of range queries. Also, Use a priority queue to speed up our process. This algorithm gives in general sub-optimal solutions with respect to search space. Our improved trajectory split algorithm is going to derive minimizing volume of EMBRs better than previously proposed split algorithm.

• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.11-19
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• 2016

In this paper, we propose an automatic segmentation method of renal parenchyma on abdominal CT image using graph-cuts with shape constraint based on multi-probabilistic atlas. The proposed method consists of following three steps. First, to use the various shape information of renal parenchyma, multi-probabilistic atlas is generated by cortex-based similarity registration. Second, initial seeds for graph-cuts are extracted by maximum a posteriori (MAP) estimation and renal parenchyma is segmented by graph-cuts with shape constraint. Third, to reduce alignment error of probabilistic atlas and increase segmentation accuracy, registration and segmentation are iteratively performed. To evaluate the performance of proposed method, qualitative and quantitative evaluation are performed. Experimental results show that the proposed method avoids a leakage into neighbor regions with similar intensity of renal parenchyma and shows improved segmentation accuracy.

• Journal of KIISE:Databases
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• v.28 no.1
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• pp.86-94
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• 2001

구형 피라미드 기법[1,2]은 d-차원의 공간을 2d개의 구형 피라미드들로 분할하는 특별한 공간 분할 방식을 이용하여 고차원 데이터를 효율적으로 색인할 수 있는 새로운 색인 방법으로 제안되었다. 구형 피라미드 기법은 구형태의 영역질의를 처리하는 알고리즘을 제안하였으나 유사 검색에 많이 사용되는 또 다른 종류의 질의인 최근접 질의를 처리하는 알고리즘을 제안하지 못했다. 본 논문에서는 점진적 최근접 질의 처리 알고리즘을 확장하여 구형피라미드 기법 상에서 효율적으로 최근접 질의를 처리하는 알고리즘을 제안한다. 마지막으로, R*-tree와 X-tree 상에서 구현된 점진적 k-최근접 질의 처리 방법과 다양한 비교 실험을 통하여 구형 피라미드 기법을 이용한 k-최근접 질의 처리 방법이 더 효율적임을 보인다.

• Spatial Information Research
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• v.19 no.2
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• pp.47-56
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• 2011

Typical tree-based spatial index structures are divided into a data-partitioning index structure such as R-Tree and a space-partitioning index structure such as KD-Tree. In recent years, researches on hybrid index structures combining advantages of these index structures have been performed extensively. However, because the split boundary extension of the node to which a new spatial object is inserted may extend split boundaries of other neighbor nodes in existing researches, overlaps between nodes are increased and the query processing cost is raised. In this paper, we propose a hybrid index structure, called SQR-Tree that can support efficient processing of spatial queries to solve these problems. SQR-Tree is a combination of SQ-Tree(Spatial Quad- Tree) which is an extended Quad-Tree to process non-size spatial objects and R-Tree which actually stores spatial objects associated with each leaf node of SQ-Tree. Because each SQR-Tree node has an MBR containing sub-nodes, the split boundary of a node will be extended independently and overlaps between nodes can be reduced. In addition, a spatial object is inserted into R-Tree in each split data space and SQ-Tree is used to identify each split data space. Since only R-Trees of SQR-Tree in the query area are accessed to process a spatial query, query processing cost can be reduced. Finally, we proved superiority of SQR-Tree through experiments.

• Journal of Korea Spatial Information System Society
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• v.7 no.1 s.13
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• pp.13-24
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• 2005

Objects, which change their positions over time such as cars, are called moving objects. Trajectories of a moving object have large volumes because trajectories are accumulated. Efficient indexing techniques for searching these large volumes of trajectories are needed in the moving object databases. Especially the TB-tree which supports bundling trajectories is suitable for processing combined queries which have 2 steps: first step is selecting trajectories (range search), next is selecting the parts of each trajectory (trajectory search). But the TB-tree has unnecessary disk accesses cause of lack of spatial discrimination in range queries. In this paper, we propose and implement the splitting polity which can reduce dead spaces of non-leaf node in order to process range queries efficiently. The policy has better performance about range queries than the TB-tree as well as the advantages of the TB-tree, such as highly space utilization and efficient trajectory extraction. This paper shows that the newly proposed split policy has better performance in processing the range queries than that of the TB-tree by experimental evaluation.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1011-1020
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• 2004

A lot of work has been done to improve the I/O performance of such a system that store and manage a massive amount of data by distributing them across multiple disks and access them in parallel. Most of the previous work has focused on an efficient mapping from a grid ceil, which is determined bY the interval number of each dimension, to a disk number on the assumption that each dimension is split into disjoint intervals such that entire data space is GRID-like partitioned. However, they have ignored the effects of a GRID partitioning scheme on declustering performance. In this paper, we enhance the performance of mapping function based declustering algorithms by applying a good GRID par-titioning method. For this, we propose an estimation model to count the number of grid cells intersected by a range query and apply a GRID partitioning scheme which minimizes query result size among the possible schemes. While it is common to do binary partition for high-dimensional data, we choose less number of dimensions than needed for binary partition and split several times along that dimensions so that we can reduce the number of grid cells touched by a query. Several experimental results show that the proposed estimation model gives accuracy within 0.5% error ratio regardless of query size and dimension. We can also improve the performance of declustering algorithm based on mapping function, called Kronecker Sequence, which has been known to be the best among the mapping functions for high-dimensional data, up to 23 times by applying an efficient GRID partitioning scheme.

• Annual Conference of KIPS
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• 2002.04a
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• pp.109-112
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• 2002

물리적 데이터베이스 설계기법은 최적의 질의처리 성능을 제공하기 위하여 데이터베이스의 액세스 구조를 결정하는 과정이다. 본 논문에서는 변환기법을 이용한 공간 액세스 구조의 물리적 데이터베이스의 설계를 위한 영역분할 전략을 제시한다. 변환기법을 이용한 공간 액세스 구조는 원공간(original space)에서의 공간 객체들을 공간의 차원을 두 배로 하는 변환공간(transformation space)내의 점 객체들로 변환하여 관리하는 방법이다. 먼저, 원공간에 주어지는 모든 공간 질의가 변환공간에서는 한가지 형태의 범위 질의로 변환되는 특징이 있음을 보인다. 그리고, 변환공간상에서 이 범의 질의가 위치하는 질의 영역의 모양과 데이터 페이지가 위치하는 페이지 영역의 모양 사이의 관련성을 이용하여 질의처리의 성능을 향상시킬 수 있는 영역분할 전략을 제안한다. 성능평가의 결과에 의하면, 주어진 질의 패턴에 따라 최적의 공간 액세스 구조를 구성할 수 있었으며, 이차원 원공간에 대한 사차원 변환 공간인 경우에 질의의 형태에 따라 질의처리의 성능이 다섯배 이상까지 향상되었다.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.396-408
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• 2006

Moving object databases manage a large amount of past location data which are accumulated as the time goes. To retrieve fast the past location of moving objects, we need index structures which consider features of moving objects. The KDB-tree has a good performance in processing range queries. Although we use the KDB-tree as an index structure for moving object databases, there has an over-split problem in the spatial domain since the feature of moving object databases is to increase the time domain. Because the over-split problem reduces spatial regions in the MBR of nodes inverse proportion to the number of splits, there has a problem that the cost for processing spatial-temporal range queries is increased. In this paper, we propose the dynamic split strategy of the KDB-tree to process efficiently the spatial-temporal range queries. The dynamic split strategy uses the space priority splitting method for choosing the split domain, the recent time splitting policy for splitting a point page to maximize the space utilization, and the last division policy for splitting a region page. We compare the performance of proposed dynamic split strategy with the 3DR-tree, the MV3R-tree, and the KDB-tree. In our performance study for range queries, the number of node access in the MKDB-tree is average 30% less than compared index structures.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.184-186
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• 2002

기존의 색인 기법들은 차원의 수가 증가할수록 검색 성능이 급격히 저하되는 문제를 지니고 있다. 이문제를 극복하기 위하여 CBF 기법이 제안되었다. 그러나 CBF 기법은 데이터 양이 증가함에 따라 검색 성능이 선형적으로 감소하는 문제가 존재한다. 이를 해결하기 위해 다수의 디스크를 수평 분할 방법을 이용하여 디클러스터링(declustering)을 하는 병렬 CBF 기법이 제안되었다. 본 논문에서는 수평 분할 방법을 이용한 병렬 CBF (Parallel CBF) 기법을 삽입시간, 범위 질의 검색시간, k-최근접 질의 검색시간, 데이터의 편중도 측면에서 성능 평가를 수행한다. 아울러, 병렬 CBF 기법을 기존 CBF 기법과 성능 비교를 수행하며, 이를 통해 병렬 CBF 기법이 기존 CBF 기법보다 우수한 검색 성능을 나타냄을 보인다.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.421-425
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• 2006

본 논문에서는 특징기반 검색을 이용하여 대용량의 비디오 데이터에 대한 사용자의 다양한 의미검색을 지원하는 에이전트 기반에서의 자동화되고 통합된 비디오 의미기반 검색 시스템을 제안한다. 사용자의 기본적인 질의를 분석하고 질의에 의해 추출된 키 프레임의 이미지를 사용자가 선택함으로써 인덱싱 에이전트는 추출된 키 프레임의 주석에 대한 의미를 더욱 구체화시킨다. 또한, 사용자에 의해 선택된 키 프레임은 특징기반 검색의 질의 이미지가 되고 인덱싱 에이전트는 제안하는 다중 분할 칼라 히스토그램 기법을 통해 질의 이미지와 데이터베이스의 키 프레임들을 비교한 후 가장 유사한 키 프레임 이미지를 검색하여 사용자에게 디스플레이한다. 제안하여 구현된 시스템은 현저히 향상된 성능을 보였다.