• 한국ITS학회 논문지
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• 제20권5호
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• pp.186-201
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• 2021

자율 주행 기술이 발전함에 따라 주행 주변 환경을 인식하는 데 차량 위치의 정확성은 매우 중요하다. 측위의 정확도를 높이기 위해 정밀지도를 사용한 지도 정합 측위기술(map-matching localization)이 연구되고 있다. 기존의 지도 정합 기법은 지도에서 차선의 중심으로 표현된 데이터를 기반으로 차량 위치를 추정하기에 차선 내 측면 거리의 편차를 반영하지 않는다. 따라서 본 논문에서는 정밀한 측위를 제공하기 위해 영상처리를 통한 차선 검출 기법과 정밀지도의 차선 위치 정보를 이용한 기법을 제안한다. 영상 처리 기법으로 IPM(inverse perspective mapping)과 다중 차선 검출 기법, 중앙선 검출 기법을 통하여 차선 번호를 검출하고 차선 이탈 감지 방법으로 차선 중심으로부터 차량의 측면 거리를 추정한다. 최종적으로 영상처리로 검출한 차선 번호와 GNSS / INS의 위치를 기반으로 정밀지도에서 위치 링크정보를 추출하고 추출된 링크에 측면 거리를 반영하여 차선 내 차량의 위치를 추정한다. 제안된 방법의 성능을 평가하기 위하여 실제 도로에서 실험하였다. 제안하는 방법은 GNSS / INS와 비교 시 약 1.0m 정도 정확도가 개선되며, 기존의 차선레벨 맵매칭 방법과 비교 시 구간별로 약 0.04m ~ 0.21m(7~30%) 정확도가 개선됨을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.1886-1908
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• 2020

With the technical advances, the amount of big data is increasing day-by-day such that the traditional software tools face a burden in handling them. Additionally, the presence of the imbalance data in big data is a massive concern to the research industry. In order to assure the effective management of big data and to deal with the imbalanced data, this paper proposes a new indexing algorithm for retrieving big data in the MapReduce framework. In mappers, the data clustering is done based on the Sparse Fuzzy-c-means (Sparse FCM) algorithm. The reducer combines the clusters generated by the mapper and again performs data clustering with the Sparse FCM algorithm. The two-level query matching is performed for determining the requested data. The first level query matching is performed for determining the cluster, and the second level query matching is done for accessing the requested data. The ranking of data is performed using the proposed Monarch chaotic whale optimization algorithm (M-CWOA), which is designed by combining Monarch butterfly optimization (MBO) [22] and chaotic whale optimization algorithm (CWOA) [21]. Here, the Parametric Enabled-Similarity Measure (PESM) is adapted for matching the similarities between two datasets. The proposed M-CWOA outperformed other methods with maximal precision of 0.9237, recall of 0.9371, F1-score of 0.9223, respectively.

• 한국측량학회지
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• 제16권2호
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• pp.203-211
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• 1998

정사투영사진 지도는 입체영상에 존재하는 공액점을 수치적으로 탐색하여 높이를 결정하는 수치사진측량 방법을 사용하여 제작되며, 공액점을 자동으로 결정하기 위한 수치영상정합 방법에 대한 많은 연구가 진행 중이다. 본 연구에서는 수치영상정합에서 공통적으로 사용되는 영상 피라미드의 4가지 축척 계수 변화와 8가지 기준영역의 크기의 변화에 따른 영역기반정합의 정확도에 미치는 영향을 고찰하였다. 각 방법에 대한 영상정합 결과는 l/5,000 수치지도 자료와 비교하였고, 영상정합의 성공률을 분석하여 최적 기준영역의 크기를 결정하였다. 수치지형모델은 결정된 영상정합 결과와 광속조정법을 이용하여 생성하였으며, 수치표고모델과 정사투영사진을 이용하여 정사투영사진 지도를 제작하였다.

• 한국정보통신학회논문지
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• 제16권3호
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• pp.407-415
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• 2012

본 논문에서는 화상회의 시스템 등 인물 위주의 스테레오 영상으로부터 깊이 정보를 추출하기 위한 스테레오 정합 기법을 제안한다. 제안한 기법에서는 두 대의 스테레오 카메라로부터 획득된 영상에서 임계값을 이용하여 배경을 먼저 제거하고, 배경이 제거된 영상과 카메라 보정을 거친 영상을 이용하여 초기 변이지도(disparity map)와 R, G, B, white 4개의 색상 성분으로 분할한 영상을 생성하게 된다. 각 색상 정보로 분할된 영상의 경계(edge) 성분을 추출하고, 추출된 경계에서 정합 창을 이용하여 변이를 추정하고 각 색상 정보의 변이지도를 적절히 조합하여 최종 변이지도를 생성하게 된다. 실험 결과 제안한 기법이 기존의 영역기반(window based) 정합기법과 동적계획법(dynamic programing method) 등보다 인물 위주의 스테레오 영상에서 더 우수한 성능을 가지는 것을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.536-538
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• 2006

The most important factor of mobile robot is to build a map for surrounding environment and estimate its localization. This paper proposes a real-time localization and map building method through 3-D reconstruction using scale invariant feature from monocular camera. Mobile robot attached monocular camera looking wall extracts scale invariant features in each image using SIFT(Scale Invariant Feature Transform) as it follows wall. Matching is carried out by the extracted features and matching feature map that is transformed into absolute coordinates using 3-D reconstruction of point and geometrical analysis of surrounding environment build, and store it map database. After finished feature map building, the robot finds some points matched with previous feature map and find its pose by affine parameter in real time. Position error of the proposed method was maximum. 8cm and angle error was within $10^{\circ}$.

• 전자공학회논문지B
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• 제32B권12호
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• pp.1591-1602
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• 1995

A hybrid approach which includes edge- and region-based methods is considered. The modified non-linear Laplacian(MNL) filter is used for feature extraction. The matching algorithm has three steps which are edge, signed region, and residual region matching. At first, the edge points are matched using the sign and direction of edges. Then, the disparity is propagated from edge to inside region. A variable window is used to consider the local method which give accurate matched points and area-based method which can obtain full-resolution disparity map. In addition, a new relaxation algorithm for considering matching possibility derived from normalized error and regional continuity constraint is proposed to reduce the mismatched points. By the result of simulation for various images, this algorithm is insensitive to noise and gives full- resolution disparity map.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1999년도 춘계학술대회 논문집
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• pp.247-250
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• 1999

In this study, three kinds of Mn-Zn ferrite/Ni-Zn ferrite/$Ni_2Y$ ferroxplana prepared by the coprecipitation method was compounded with silicon rubber, and thereafter made ring-type specimens with various compositional ratio. The material constant of ferrite/rubber composite absorbers was obtaibed by the 2-port method. The material constants of the ferrite/rubber composite absorber with various compositional ratio of three kinds of ferrite were used to design the matching frequency and thickness with the impedance matching map. We were able to predict the matching condition from the design method.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1281-1287
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• 2016

This paper presents a method of single image dehazing and feature matching for aerial remote sensing images. In the case of a aerial image, transferring the information of the original image is difficult as the contrast leans by the haze. This also causes that the image contrast decreases. Therefore, a refined transmission map based on a hidden Markov random field. Moreover, the proposed algorithm enhances the accuracy of image matching surface-based features in an aerial remote sensing image. The performance of the proposed algorithm is confirmed using a variety of aerial images captured by a Worldview-2 satellite.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.159-162
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• 2002

This paper presents a modified localization scheme of a mobile robot. When it navigates, the position error of a robot is increased and doesn't go to a goal point where the robot intends to go at the beginning. The objective of localization is to estimate the position of a robot precisely. Many algorithms were developed and still are being researched for localization of a mobile robot at present. Among them, a localization algorithm named continuous localization proposed by Schultz has some merits on real-time navigation and is easy to be implemented compared to other localization schemes. Continuous Localization (CL) is based on map-matching algorithm with global and local maps using only ultrasonic sensors for making grid maps. However, CL has some problems in the process of searching the best-scored-map, when it is applied to a mobile robot. We here propose fast and powerful map-matching algorithm for localization of a mobile robot by experiments.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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• pp.131-136
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• 1997

We present a method to estimate a dense and sharp depth map using multiple cameras for the application to flexible video production. A key issue for obtaining sharp depth map is how to overcome the harmful influence of occlusion. Thus, we first propose to selectively use the depth information from multiple cameras. With a simple sort and discard technique, we resolve the occlusion problem considerably at a slight sacrifice of noise tolerance. However, boundary overreach of more textured area to less textured area at object boundaries still remains to be solved. We observed that the amount of boundary overreach is less than half the size of the matching window and, unlike usual stereo matching, the boundary overreach with the proposed occlusion-overcoming method shows very abrupt transition. Based on these observations, we propose a hierarchical estimation scheme that attempts to reduce boundary overreach such that edges of the depth map coincide with object boundaries on the one hand, and to reduce noisy estimates due to insufficient size of matching window on the other hand. We show the hierarchical method can produce a sharp depth map for a variety of images.