• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1053-1059
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• 2010

This paper treats the DIS (Digital Image Stabilization) problem subject to base motions such as translation, rotation and zoom. For the local motion estimation from a raw image, the Harris corner detection algorithm is exploited to extract feature points, and comparing those of consecutive images, the zoom ratio (scale factor) is computed. For the global motion estimation, an equivalent model is derived to account for a 3-dimensional composite motion from which the center point and Euler angle can be determined. Finally, the motion compensation follows. To show the effectiveness of the present DIS scheme, experimental results for synthetic images are illustrated.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.700-702
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• 2004

모자이크는 설러 장의 영상을 하나의 큰 영상으로 만드는 것을 말한다. 본 논문은 asymmetrical closing이라고 불리는 모폴로지에 의한 closing operator를 사용한 영상 모자이크에 관한 연구이다. asymmetrical closing을 하기 위한 structuring element를 소개하고 이것을 이용한 코너 정 추출 방법 및 local maxima에 대해서도 소개한다. 여러 개의 코너 정들 중 조건을 만족하는 tie point들을 이용하여 Perspective 변환 파라미터를 추출하여 최종 모자이크 결과 영상을 생성하게 된다.

• Journal of Internet Computing and Services
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• v.6 no.5
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• pp.85-95
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• 2005

This study proposes a method of feature point extraction using scale-space filtering and a feature point tracking algorithm based on a texturedness similarity comparison, With well-defined operators one can select a scale parameter for feature point extraction; this affects the selection and localization of the feature points and also the performance of the tracking algorithm. This study suggests a feature extraction method using scale-space filtering, With a change in the camera's point of view or movement of an object in sequential images, the window of a feature point will have an affine transform. Traditionally, it is difficult to measure the similarity between correspondence points, and tracking errors often occur. This study also suggests a tracking algorithm that expands Shi-Tomasi-Kanade's tracking algorithm with texturedness similarity.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1162-1170
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• 2018

This paper presents an augmented reality system for multiple users. The proposed system performs ar image-based pose estimation of users and pose of each user is shared with other uses via a network server. For camera-based pose estimation, we install multiple markers in a pre-determined space and select the marker with the best appearance. The marker is detected by corner point detection and for robust pose estimation. the marker's corner points are tracked by optical flow tracking algorithm. Experimental results show that the proposed system successfully provides an augmented reality application to multiple users even when users are rapidly moving and some of markers are occluded by users.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.3
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• pp.457-463
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• 2011

As computer related technologies are developed, interests in augmented reality technologies are greatly increasing. Augmented reality is a technology that composes digital contents from the real input images through camera and it enables interaction with users. This study designed a directional marker using LED light that emits infrared ray, then, provided a detection algorithm and a marker information extraction method that can realize various virtual objects as augmented reality from one marker. The newly designed method provides a solution to settle the problems in existing marker technologies such as decrease of immersiveness and read rate and single information expression, and at the same time it can minimize the cost or time consumption in marker information storage.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.479-493
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• 2016

LiDAR(Light Detection and Ranging) data acquired from ALS(Airborne Laser Scanner) has been intensively utilized to reconstruct object models. Especially, researches for 3D modeling from LiDAR data have been performed to establish high quality spatial information such as precise 3D city models and true orthoimages efficiently. To reconstruct object models from irregularly distributed LiDAR point clouds, sensor calibration, noise removal, filtering to separate objects from ground surfaces are required as pre-processing. Classification and segmentation based on geometric homogeneity of the features, grouping and representation of the segmented surfaces, topological analysis of the surface patches for modeling, and accuracy assessment are accompanied by modeling procedure. While many modeling methods are based on the segmentation process, this paper proposed to extract key points directly for building modeling without segmentation. The method was applied to simulated and real data sets with various roof shapes. The results demonstrate feasibility of the proposed method through the accuracy analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.69-72
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• 2011

In this paper, we propose a method to track the movement of camera from the video sequences. This method is useful for video analysis and can be applied as pre-processing step in some application such as video stabilizer and marker-less augmented reality. First, we extract the features in each frame using corner point detection. The features in current frame are then compared with the features in the adjacent frames to calculate the optical flow which represents the relative movement of the camera. The optical flow is then analyzed to obtain camera movement parameter. The final step is camera movement estimation and correction to increase the accuracy. The method performance is verified by generating a 3D map of camera movement and embedding 3D object to the video. The demonstrated examples in this paper show that this method has a high accuracy and rarely produce any jitter.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.133-139
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• 2013

This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.150-150
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• 1999

In this paper, a content-based image retrieval scheme based on scale-space theory is proposed. The existing methods using scale-space theory consider all scales for image retrieval,thereby requiring a lot of computation. To overcome this problem, the proposed algorithm utilizes amodified histogram intersection method to select candidate images from database. The relative scalebetween a query image and a candidate image is calculated by the ratio of histograms. Feature pointsare extracted from the candidates using a corner detection algorithm. The feature vector for eachfeature point is composed of RGB color components and differential invariants. For computing thesimilarity between a query image and a candidate image, the euclidean distance measure is used. Theproposed image retrieval method has been applied to various images and the performance improvementover the existing methods has been verified.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.165-168
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• 2016

카메라 캘리브레이션은 실제 세상인 3차원의 좌표와 카메라가 만든 영상의 2차원 좌표 사이에서 수학적 관계를 알기 위해서 필요하다. 보통 체커보드의 교점을 이용하여 2차원의 좌표를 정확하게 찾는데 사용하며, 이는 카메라 캘리브레이션 계산으로 응용된다. 따라서 체커보드의 교점을 정확하게 찾아야만 카메라 캘리브레이션이 정상적인 성능을 낼 수 있다. 현존하는 체커보드 검출 방법은 입력 인수를 많이 필요로 하거나 정확도가 낮아 체커보드의 교점을 정확히 입력하지 못하면 좋지 않은 결과가 나타난다. 따라서 체커보드를 자동으로 검출하여 카메라 캘리브레이션 하는 방법은 아직 신뢰도가 낮은 편이다. 본 논문에서는 보다 안정적인 카메라 캘리브레이션을 위해서 체커 보드의 검출 성능을 높이고자 한다. 주위 픽셀들간의 미분 값을 기준삼아 검출된 교점들을 이용하여 체크 모양의 직선을 추측한다. 이 직선을 이용하면 장애물이 있거나 노이즈가 있어서 검출하기 어려운 교점들이 있는 경우에도 교점 보간 (point interpolation) 방법을 사용하여 나머지 교점들을 찾을 수 있다. 보간 과정을 통해서 검출에 방해가 되는 요소들이 있는 상황에서 체커 보드 교점 검출의 성능을 높이도록 하였다.