• Spatial Information Research
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• v.13 no.1 s.32
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• pp.55-63
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• 2005

Direct Georeferencing(DG) Is based on the direct measurement of the projection centers and rotation angle of sensor through loading the GPS and INS in aircraft. The methods can offer us to acquire the exterior orientation parameters with only minimum GCPs, even the ground control process could be completely skipped. Hence, as long as securing Digital Elevation Model (DEM), it is feasible to generate digital orthophotos without performing the aerial triangulation with Ground Control Point (GCP) surveying. In this study, the DEM is automatically generated by using a image matching technique based on aerial photos and exterior orientation parameters. This is followed by producing an orthophoto from these results. Finally, accuracy analysis of the georeferencing technique for generating orthoimage indicates that RMS errors of 62cm and 76cm occurred at the X and the Y axis, respectively. This means that the results fulfill the demanding accuracy of the 1:5000 digital map. Hence, it is possible to conclude from this study that the direct georeferencing based orthoimage generation method is able to effectively digital map update.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.1
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• pp.21-27
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• 2002

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. A number of visual or optical technologies have been successfully applied to measure three-dimensional surfaces. However, those conventional visual or optical methods have inherent shortcomings such as occlusion and variant surface reflection. X-ray vision system can be a good solution to these conventional problems, since we can extract the volume information including both the surface geometry and the inner structure of any objects. In the x-ray system, the surface condition of an object, whether it is lambertian or specular, does not affect the inherent characteristics of its x-ray images. In this paper, we propose a three-dimensional x-ray imaging method to reconstruct a three dimensional structure of an object out of two dimensional x-ray image sets. To achieve this by the proposed method, two or more x-ray images projected from different views are needed. Once these images are acquired, the simultaneous algebraic reconstruction technique(SART) is usually utilized. Since the existing SART algorithms have several shortcomings such as low performance in convergence and different convergence within the reconstruction volume of interest, an advanced SART algorithm named as USART(uniform SART) is proposed to avoid such shortcomings and improve the reconstruction performance. Because, each voxel within the volume is equally weighted to update instantaneous value of its internal density, it can achieve uniform convergence property of the reconstructed volume. The algorithm is simulated on various shapes of objects such as a pyramid, a hemisphere and a BGA model. Based on simulation results the performance of the proposed method is compared with that of the conventional SART method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.59-69
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• 2007

In the video with a various environment, background modeling is important for extraction and recognition the moving object. For this object recognition, many methods of the background modeling are proposed in a process of preprocess. Among these there is a Kumar method which represents the Queue-based background modeling. Because this has a fixed period of updating examination of the frame, there is a limit for various system. This paper use a background modeling based on the queue. We propose the method that major parameters are decided as adaptive by background model. They are the queue size of the sliding window, the sire of grouping by the brightness of the visual and the period of updating examination of the frame. In order to determine the factors, in every process, RCO (Ratio of Correct Object), REO (Ratio of Error Object) and UR (Update Ratio) are considered to be the standard of evaluation. The proposed method can improve the existing techniques of the background modeling which is unfit for the real-time processing and recognize the object more efficient.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.55-62
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• 2013

This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.2
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• pp.119-126
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• 2002

Recently, as advancing the technologies for Web 3D and Virtual Reality, the studies have been progressed actively to provide three dimensional information on the web. Especially, the various applications for providing urban information in 3D space have been developed using EAI(External Authoring Interface) that serves an interface between VRML(Virtual Reality Modeling Language), standard language for embodying virtual reality, and JAVA applet in HTML. In this study, as constructing 3D virtual city information using Digital Map, IKONOS satellite image, VRML and so on, we could provide users which need several information with building location and various urban living information. In addition, applying 3D skills such as texturing, panorama and navigation, users were enabled to perform various route searching and scenery analysis. Finally, to serve urban living information in real time, we designed to search information faster through interfacing database and to update data using ASP(Active Server Page) on web.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.366-369
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• 2005

Background subtraction is mainly used for the real-time extraction and tracking of moving objects from image sequences. In the outdoor environment, there are many changeable factor such as gradually changing illumination, swaying trees and suddenly moving objects, which are to be considered for the adaptive processing. Normally, GMM(Gaussian Mixture Model) is used to subtract the background adaptively considering the various changes in the scenes, and the adaptive GMMs improving the real-time performance were worked. This paper, for on-line background subtraction, applied the improved adaptive GMM, which uses the small constant for learning rate ${\alpha}$ and is not able to speedily adapt the suddenly movement of objects, So, this paper proposed and evaluated the dynamic control method of ${\alpha}$ using the adaptive selection of the number of component distributions and the global variances of pixel values.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.436-443
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• 2009

There have been rapid increases to the demands for modeling diverse and complex spatial phenomena and utilizing spatial data through the computer across all the aspects of society. As a result, the importance and utilization of remote sensing and GIS's(geographic information systems) have also increased. It can produce digital data of enormous accuracy and value by incorporating remote sensing images into GIS analysis technology and make various thematic maps by classifying and analyzing land cover. Once such a map is made for the target area, it can easily do modeling and constant monitoring based on the map, revise the database with ease, and thus efficiently update geo-spatial information. Under the goal of analyzing changes to land cover along the road by combining the remote sensing and GIS technology, this study classified land cover from the images of two periods, detected changes to the six classes over ten years, and obtained statistics about the study area's quantitative area changes in order to provide basic decision making data for urban planning and development. By analyzing land use along the road, one can set up plans for the area along the road and the downtown to supplement each other.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1152-1157
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• 2021

This paper proposes a face recognition method for access control of apartment building. Different from most existing face recognition methods, the proposed one does not require any manual process for face enrollment. When a person is exiting through the main entrance door, his/her face data (i.e., face image and face feature) are automatically extracted from the captured video and registered in the database. When the person needs to enter the building again, the face data are extracted and the corresponding face feature is compared with the face features registered in the database. If a matching person exists, the entrance door opens and his/her access is allowed. The face data of the matching person are immediately deleted and the database has the latest face data of outgoing person. Thus, a higher recognition accuracy could be expected. To verify the feasibility of the proposed method, Python based face recognition has been implemented and the cloud service provided by a web portal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.587-588
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• 2022

In this paper, we propose a rigid body tracking method in 3D space using 2D passive marker images from multiple motion capture cameras. First, a calibration process using a chess board is performed to obtain the internal variables of individual cameras, and in the second calibration process, the triangular structure with three markers is moved so that all cameras can observe it, and then the accumulated data for each frame is calculated. Correction and update of relative position information between cameras. After that, the three-dimensional coordinates of the three markers were restored through the process of converting the coordinate system of each camera into the 3D world coordinate system, the distance between each marker was calculated, and the difference with the actual distance was compared. As a result, an error within an average of 2mm was measured.