• The KIPS Transactions:PartD
• /
• v.11D no.7 s.96
• /
• pp.1385-1398
• /
• 2004

This paper discusses an effective processing of subsequence matching under time warping in time-series databases. Time warping is a trans-formation that enables finding of sequences with similar patterns even when they are of different lengths. Through a preliminary experiment, we first point out that the performance bottleneck of Naive-Scan, a basic method for processing of subsequence matching under time warping, is on the CPU processing step. Then, we propose a novel method that optimizes the CPU processing step of Naive-Scan. The proposed method maximizes the CPU performance by eliminating all the redundant calculations occurring in computing the time warping distance between the query sequence and data subsequences. We formally prove the proposed method does not incur false dismissals and also is the optimal one for processing Naive-Scan. Also, we discuss the we discuss to apply the proposed method to the post-processing step of LB-Scan and ST-Filter, the previous methods for processing of subsequence matching under time warping. Then, we quantitatively verify the performance improvement ef-fects obtained by the proposed method via extensive experiments. The result shows that the performance of all the three previous methods im-proves by employing the proposed method. Especially, Naive-Scan, which is known to show the worst performance, performs much better than LB-Scan as well as ST-Filter in all cases when it employs the proposed method for CPU processing. This result is so meaningful in that the performance inversion among Nive- Scan, LB-Scan, and ST-Filter has occurred by optimizing the CPU processing step, which is their perform-ance bottleneck.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.1
• /
• pp.45-52
• /
• 2015

The interoperability of multi-source data has become more important due to various digital maps, produced from public institutions and enterprises. In this study, the automatic matching algorithm of multi-source building data using hierarchical matching was proposed. At first, we divide digital maps into blocks and perform the primary geometric registration of buildings with the ICP algorithm. Then, corresponding building pairs were determined by evaluating the similarity of overlap area, and the matching threshold value of similarity was automatically derived by the Otsu binary thresholding. After the first matching, we extracted error matching candidates buildings which are similar with threshold value to conduct the secondary ICP matching and to make a matching decision using turning angle function analysis. For the evaluation, the proposed method was applied to representative public digital maps, road name address map and digital topographic map 2.0. As a result, the F measures of matching and non-matching buildings increased by 2% and 17%, respectively. Therefore, the proposed method is efficient for the matching of building polygons from multi-source digital maps.

• Korean Journal of Remote Sensing
• /
• v.38 no.3
• /
• pp.283-298
• /
• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.6
• /
• pp.1313-1320
• /
• 2015

In this paper, we propose a user detection technique based on parallel orthogonal matching pursuit (POMP) for uplink multi-user random access networks (RANs) with a number of users and receiver antennas. In general RANs, it is difficult to estimate the number of users simultaneously transmitting packets at the receiver because users with data send the data without grant of BS. In this paper, therefore, we modify the original POMP for the RAN and evaluate its performances through extensive computer simulations. Simulation results show that the proposed POMP can effectively detect activated users more than about 2%~8% compared with the conventional OMP in RANs.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2007.11a
• /
• pp.479-486
• /
• 2007

멘토링은 조직이나 사회 구성원들의 발전을 돕기 위한 프로그램으로서, 조언자, 상담자 및 후원자 역할을 하는 '멘토(mentor)'와 도움을 얻고자 하는 '멘티(mentee)'가 긴밀한 관계를 맺고 유지함으로써 상호 발전을 위해 수행된다. 현재 이루어지고 있는 대부분의 멘토링은 면대면 (face-to-face) 시스템이거나 웹 기반의 e-mentoring 시스템으로, 전자는 시간적 그리고 지역적 한계를 극복해야만 하고 후자는 멘토나 멘티가 멘토링 사이트에 접속하여 게시판을 확인하지 않으면 제대로 된 멘토링을 수행할 수 없다는 한계를 가지고 있다. 또한 멘토와 멘티의 매칭은 무작위로 이루어지거나 코디네이터라고 불리는 사람이 수행하기 때문에, 비용이 많이 소용될 뿐 아니라 개인적인 편견이나 오류가 개입될 여지가 상존한다. 이에 본 연구에서는 시간과 장소의 제약에 구애 받지 않는 u-Mentoring 시스템을 개발하고자 하며, 그 첫 단계로써 멘토와 멘티간의 매칭을 지원하는 새로운 알고리즘(M3 Algorithm, Mentor-Mentee Matching Algorithm)을 제안하고자 한다. 본 연구에서 제안하는 알고리즘은 매칭의 정확도와 멘토-멘티의 매칭 만족도를 높이기 위해 멘토-멘티 온톨로지(M-Ontology)와 사례기반추론 기법을 사용하였다. 즉, 멘토-멘티의 효과적인 매칭을 위해, 멘토-멘티간 매칭 사례가 없는 초기 단계에는 멘토와 멘티의 속성 비교를 통한 추천 방식을 사용하고, 멘토링이 종료되어 충분한 멘토-멘티간 매칭사례가 수집되면 그 결과를 재사용해 추후 매칭에 활용한다. 본 논문에서는 제안한 매칭 알고리즘이 내장된 u-Mentoring system의 포로토타입을 보여주고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.07a
• /
• pp.303-304
• /
• 2011

영역기반 스테레오 매칭의 분야에서 최근 인간의 시각체계(Human Visual System)에 기반하여 영역내의 밝기값과 거리값에 따라 적응적으로 가중치를 부여하는 적응적 영역 가중치(Adaptive Support-Weight) 방법이 좋은 매칭 결과를 보이고 있다. 하지만 이 방법은 영역 윈도우의 크기가 커짐에 따라 기하급수적으로 계산량이 많아지는 단점을 보이고 있다. 이에 Bilateral filter 수식으로 근사화 후 Integral Histogram 기법을 적용하여 영역 윈도우의 크기에 상관없이 상수 시간 O(1) 내에 매칭을 수행하는 연구가 진행되었다. 하지만 이 방법은 근사화 과정에서의 원 ASW 수식을 왜곡하기 때문에 매칭 정확도의 손실을 가져오게 된다. 이에 본 논문에서는 Bilateral 접근 방식, Sub-Block 방식 및 적응적 시차 탐색 방식에 대하여 각 방식에서 필요한 메모리 자원과 소모되는 계산량의 비용과 동시에 매칭 결과 정확도 면에서 비교하고 가장 좋은 접근 방식을 도출하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.04a
• /
• pp.125-128
• /
• 2015

최근 GPS가 기본 탑재된 스마트폰이 활성화된 이후 대량의 GPS 궤적 데이터를 전자지도에 매칭하여 분석하는 요구가 대두되고 있다. 그러나 기존에 연구된 맵매칭 기법은 주로 내비게이션용 알고리즘으로 대량의 GPS궤적을 서버에서 분석하기에는 속도 및 시스템 성능의 이슈가 있다. 본 연구는 대표적인 분산 NoSQL DB인 하듐 에코시스템의 HBase를 이용한 맵매칭 시스템에 대한 연구이다. 맵매칭을 위한 전자지도를 HBase탑재하기 위한 테이블 사양을 정의하였고, HBase와 연동하여 분석하는 맵매칭 알고리즘을 제시하고 Java로 구현하여 분석하였다. 이를 통해 대량의 GPS궤적을 NoSQL 기반 방법론을 통하여 효율적으로 빅데이터를 분석하였다.

• The KIPS Transactions:PartD
• /
• v.12D no.3 s.99
• /
• pp.345-354
• /
• 2005

Subsequence matching is one of the most important operations in the field of data mining. The existing subsequence matching algorithms use only one index, and their performance gets worse as the difference between the length of a query sequence and the site of windows, which are subsequences of a same length extracted from data sequences to construct the index, increases. In this paper, we propose a new subsequence matching method based on index interpolation to overcome such a problem. An index interpolation method constructs two or more indexes, and performs search ing by selecting the most appropriate index among them according to the given query sequence length. In this paper, we first examine the performance trend with the difference between the query sequence length and the window size through preliminary experiments, and formulate a search cost model that reflects the distribution of query sequence lengths in the view point of the physical database design. Next, we propose a new subsequence matching method based on the index interpolation to improve search performance. We also present an algorithm based on the search cost formula mentioned above to construct optimal indexes to get better search performance. Finally, we verify the superiority of the proposed method through a series of experiments using real and synthesized data sets.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.2C
• /
• pp.201-208
• /
• 2003

The error concealment is very useful technique for real-time communication, such as video conference. In this paper. we propose the error concealment technique to minimize discontinuity of block boundary in consideration of the fact that human visual system is sensitive to discontinuity. The error concealment for each loss block is performed by extended block matching method based on gradient difference. In the simulation result, performance improvement for the proposed technique is on the average 1.32㏈ in comparison with the conventional technique.

• Journal of Biomedical Engineering Research
• /
• v.24 no.4
• /
• pp.339-346
• /
• 2003

MRI provides anatomical structure information with superb spatial resolution that can be utilized in clinical surgeries. Advanced image processing techniques in conjunction with the MRI-guided surgery is expected to be of great importance in brain surgeries in the near future. In this paper, we introduce an image-guided surgery technique using the stereo matching method. To perform image-guided biopsy operations, we made MRI markers, camera markers and a detection probe marker. To evaluate the accuracy of the image-guided system. we made a silicone phantom. Using the phantom and markers, we have performed MRI-guided experiments with a 1.5 Tesla MRI system. It has been verified from phantom experiments that our system has a positioning error less than 1.5%. Compared with other image guided surgery system, our system shows better positioning accuracy.