• 전자공학회지
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• 제23권12호
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• pp.115-125
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• 1996

This paper presents a new algorithm for the self-localization of a mobile robot using one degree perspective Invariant(Cross Ratio). Most of conventional model-based self-localization methods have some problems that data structure building, map updating and matching processes are very complex. Use of a simple cross ratio can be effective to the above problems. The algorithm is based on two basic assumptions that the ground plane is flat and two locally parallel sloe-lines are available. Also it is assumed that an environmental map is available for matching between the scene and the model. To extract an accurate steering angle for a mobile robot, we take advantage of geometric features such as vanishing points. Feature points for cross ratio are extracted robustly using a vanishing point and intersection points between two locally parallel side-lines and vertical lines. Also the local position estimation problem has been treated when feature points exist less than 4points in the viewed scene. The robustness and feasibility of our algorithms have been demonstrated through real world experiments In Indoor environments using an indoor mobile robot, KASIRI-II(KAist Simple Roving Intelligence).

• 한국소음진동공학회논문집
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• 제26권5호
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• pp.609-615
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• 2016

Measuring similarity between two signals is a key element of the location template matching (LTM) method which is one of impact source localization technique. As a measure of similarity, the correlation coefficient is most widely used, and the group delay based method is recently proposed to improve the accuracy of finding the impact source. In practice, the LTM method assumes that the similarity between two signals decreases as the distance between two corresponding impact points increases, where the distance between two neighboring impact points defines the grid spacing. In this paper, it is shown that this assumption is not always true but the correlation coefficients fluctuate forming a main robe and many side robes as the distance between two neighboring impact points increases. On the other hand, the standard deviation of group delay sharply increases with a small increase of the grid spacing. These are demonstrated by using a simple cantilever beam. Based on these findings, an optimal way of implementing the LTM method may be suggested by combining the correlation coefficient and the group delay based approaches.

• 디지털콘텐츠학회 논문지
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• 제5권4호
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• pp.257-263
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• 2004

본 논문은 객체 기반 스테레오 정합에 있어서, 분할영역 내부에 존재하는 단계적인 변위의 변화를 추정할 수 있는 스테레오 정합 알고리즘에 관한 것이다. 우산 분할영역을 효과적으로 표현할 수 있는 복수의 샘플점들을 선정한 다음에 각 샘플점 주위에 인접한 영역 내부의 미소영역을 취하여 스테레오 정합을 수행한다. 이후, 선택된 각 샘플점의 변위에 의한 평면의 방정식을 이용하여 내부 변위들을 보간한다. 제안된 방법에 따르면, 샘플점에서 얻어진 변위 값을 영역내부로 전파시킴으로써 깊이 추정이 단지 특징점들에서만 국한되는 특징 기반 기법의 문제점을 해결할 수 있으며, 또한 분할영역의 외곽선에서 샘플점을 추출함으로써 단순 영역에서의 깊이 추정이 모호하게 되는 영역기반 기법의 문제점을 효과적으로 억제시킬 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1175-1180
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• 1991

The purpose of this paper is to improve the matching accuracy in identifying corresponding points in the area-based matching for the processing of stereo vision. For the selection of window size, a new method is proposed based on frequency domain analysis. The effectiveness of the proposed method is confirmed through a series of experiments. To overcome disproportionate distortion in stereo image pair, a new matching method using the warped window is also proposed. In the algorithm, the window is warped according to imaging geometry. Experiments on a synthetic image show that the matching accuracy is improved by 14.1% and 4.2% over the rectangular window method and image warping method each.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
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• pp.9-12
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• 2001

Point pattern matching schemes for finger print recognition do not guarantee robust matching performance for finger print images of poor quality. We present a finger print recognition scheme, where transformation parameter of matched ridge pairs are estimated by Hough transform and the matching hypothesis is verified by a new measure of the matching degree using selective directional information. Proposed method may exhibit extremely low FAR(False Accept Ratio) while maintaining low reject ratio even for the images of poor quality because of the robustness to the variation of minutia points.

• 제어로봇시스템학회논문지
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• 제8권4호
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• pp.327-332
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• 2002

The main problems of computational complexity in object tracking are definition of objects, segmentations and identifications in non-structured environments with erratic movements and collisions of objects. The object's information as a region that corresponds to objects without discriminating among objects are considered. This paper describes the algorithm that, automatically and efficiently, recognizes and keeps tracks of interest-regions selected by users in video or camera image sequences. The block-based feature matching method is used for the region tracking. This matching process considers only dominant feature points such as corners and curved-edges without requiring a pre-defined model of objects. Experimental results show that the proposed method provides above 96% precision for correct region matching and real-time process even when the objects undergo scaling and 3-dimen-sional movements In successive image sequences.

• 대한원격탐사학회지
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• 제36권4호
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• pp.545-555
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• 2020

This paper focuses on automatic image registration between EO (Electro-Optical) and IR (InfraRed) satellite images with different spectral properties using block-based approach and simple preprocessing technique to enhance the performance of feature matching. If unpreprocessed EO and IR images from Kompsat-3A satellite were applied to local feature matching algorithms(Scale Invariant Feature Transform, Speed-Up Robust Feature, etc.), image registration algorithm generally failed because of few detected feature points or mismatched pairs despite of many detected feature points. In this paper, we proposed a new image registration method which improved the performance of feature matching with block-based registration process on 9-divided image and pre-processing technique based on adaptive histogram equalization. The proposed method showed better performance than without our proposed technique on visual inspection and I-RMSE. This study can be used for automatic image registration between various images acquired from different sensors.

• 대한원격탐사학회지
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• 제16권4호
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• pp.347-353
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• 2000

The purpose of this paper is to extract DEM (Digital Elevation Model) using KOMPSAT images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding points of them and third part is to calculate the elevation of each point by using the result of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. Area based matching method is used to find the corresponding points between the stereo satellite images. The elevation of each point is calculated using the exterior orientation information obtained from sensor modeling and the disparity from the stereo matching. In experiment, the KOMPSAT images, 2592$\times$2796 panchromatic images are used to extract DEM. The experiment result show the DEM using KOMPSAT images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.3011-3024
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• 2021

Pose estimation of the sensor is important issue in many applications such as robotics, navigation, tracking, and Augmented Reality. This paper proposes visual-inertial integration system appropriate for dynamically moving condition of the sensor. The orientation estimated from Inertial Measurement Unit (IMU) sensor is used to calculate the essential matrix based on the intrinsic parameters of the camera. Using the epipolar geometry, the outliers of the feature point matching are eliminated in the image sequences. The pose of the sensor can be obtained from the feature point matching. The use of IMU sensor can help initially eliminate erroneous point matches in the image of dynamic scene. After the outliers are removed from the feature points, these selected feature points matching relations are used to calculate the precise fundamental matrix. Finally, with the feature point matching relation, the pose of the sensor is estimated. The proposed procedure was implemented and tested, comparing with the existing methods. Experimental results have shown the effectiveness of the technique proposed in this paper.

• 전자공학회논문지CI
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• 제48권2호
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• pp.55-65
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• 2011

본 논문은 증강현실 시스템에서 마커가 가려진 상황에서도 강건한 마커 검출을 위하여 지역적인 특징 점들을 이용하는 방법을 제안한다. 가려진 마커를 효율적으로 검출하기 위하여, 첫 번째 단계로 등록된 마커와 가려진 마커가 포함된 입력 영상을 Affine-SIFT (ASIFT, Affine-Scale Invariant Features Transform) 방법을 이용해 정합된 특징 점들을 검출한다. 두 번째 단계로 정합된 특징 점들의 이상치(Outlier)를 제거하기 위하여, 등록된 마커의 특징 점들에 주성분 분석(Principal Component Analysis)을 적용하고 제 1 주축과 제 2 주축으로 사영한 후 중심으로 부터의 거리에 대한 평균값을 타원의 장축과 단축으로 지정한다. 세 번째 단계로 마커의 기하학적인 왜곡을 추정하기 위하여 특징 점들이 이루는 Convex-hull 지점들을 다각형의 꼭짓점으로 정한다. 마지막 단계로, 입력영상에 정합된 특징 점들의 기하적인 왜곡의 변화를 추정함으로써 마커의 가려진 환경에 서도 강건한 마커 검출 결과를 얻을 수 있다.