• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.12
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• pp.659-666
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• 2000

A stereo matching has been an important tool for reconstructing three dimensional terrain. By using stereo matching technique, DEM(Digital Elevaton Map) can be generated by the disparity from a reference image to a target image. Generally disparity map can be evaluated by matching the reference image to the target image and if the role of the reference and the target are interchanged, a different DEM can be obtained. In this paper, we propose a new fusion technique to estimate the optimal DEM by eliminating the false DEM due to occlusion. To detect the false DEM, we utilize two measure of accuracy: self-consistency and cross-correlation score. We test the effectiveness of the proposed methods with a quantitative analysis using simulated images. Experimental result indicate that the proposed methods show 24.4% and 33.1% improvement over either DEM.

• Journal of Cadastre & Land InformatiX
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• v.44 no.1
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• pp.127-138
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• 2014

It can be effective to extract and apply the updated information from the newly updated map data for updating road data of topographic map. In this study, update target data and update reference data are overlaid and the update objects are explored using network matching technique. And the network objects are classified into five matching and update cases and the update processes for each case are applied to the test data. For this study, road centerline data of digital topographic map is used as an update target data and road data of Korean Address Information System is used as an update reference data. The buffer-based network matching method is applied to the two data and the matching and update cases are classified after calculating the overlaid ratio of length. The newly updated road centerline data of digital topographic map is generated from the application of update process for each case. As a result, the update information can be extracted from the different map dataset and applied to the road network data updating.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.101-108
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• 2012

The construction of data connection is required due to the digital map do not have the new address data which is implemented by the Korea government and it cannot use between government and other agency. The manually matching of digital map and new address data is time and money consuming process due to the huge amount of data. In this research, new system is developed for data generation of attribute data by the data connection method of digital map and new address data using spatial matching and matching rate of data connection is analyses. The results of data matching rate in the research area are 84% in building case and 67% in road case in 1:1000 digital map at Suwon and 18% in building case and 21% in road at Seogwipo.

• Journal of Korean Society for Geospatial Information Science
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• v.3 no.2 s.6
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• pp.213-220
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• 1995

Map Matching is the method for correcting the current position from dead reckoning in Car Navigation System. In this paper, we proposed the new map matching algorithm that can correct the positioning error caused by sensors and digital map data around the cross road area. To do this, first we set the error boundary of the cross road area by combining the relative error of moving distance and the absolute error of road length, second, we find out the starting point of turning within the determined error boundary of the cross point area, third, we compare the turning angle of the car to the angle of each possible road, and the last, we decide the matched road. We used wheel sensor as a speed sensor and used optical fiber gyro as a directional sensor, and assembled the sensors to the notebook computer. We testified our algorithm by driving the Daejeon area-which is a part of south Korea-as a test area. And we proved the efficiency by doing that.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.3-4
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• 2010

Map integration usually involves matching the common spatial objects in different datasets. There have been recent studies on object matching using relative location as defined by spatial relationships between the object and its neighbor landmark. Therefore the landmark selection process is an important part of map integration using relative location. In this research, we describe an approach to determine landmarks automatically in different geospatial datasets.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.5
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• pp.36-42
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• 2002

This paper presents the way of building an occupancy grid map which a mobile robot needs to autonomously navigate in the unknown environment. A disparity map resulting from stereo matching can be converted into the 2D distance information. If the stereo matching has some errors, however, the subsequent map becomes unreliable. In this paper, a new morphological filter is proposed to reject 'spikes' of the disparity map due to stereo mismatch by considering the fact that these spikes occur locally. The new method has advantages that it is simpler and more easily realized than existing similar algorithms. Several occupancy grid maps based on stereo vision using the proposed algorithm have been built and compared with the actual distance information to verify the validity of the proposed method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.418-422
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• 2009

Generally, algorithms for generating disparity maps can be clssified into two categories: region-based method and feature-based method. The main focus of this research is to generate a disparity map with an accuracy depth information for 3-dimensional reconstructing. Basically, the region-based method and the feature-based method are simultaneously included in the proposed algorithm, so that the existing problems including false matching and occlusion can be effectively solved. As a region-based method, regions of false matching are extracted by the proposed MMAD(Modified Mean of Absolute Differences) algorithm which is a modification of the existing MAD(Mean of Absolute Differences) algorithm. As a feature-based method, the proposed method eliminates false matching errors by calculating the vector with SIFT and compensates the occluded regions by using a pair of adjacent SIFT matching points, so that the errors are reduced and the disparity map becomes more accurate.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.965-971
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• 2015

This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.141-146
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• 2003

In case of producing image map by using the color aerial photograph, DEM makes on huge effects to the accuracy of ortho image. Thus, this paper has the purpose that evaluate the accuracy of DEM acquired by matching the color aerial photograph. At the study, result of color aerial photograph's control point surveying was X=${\pm}$0.14m, f=${\pm}$0.16m. Estimated result by DEM of plot-map and matching has RMSE=${\pm}$1.058m for the elevation(Z). For matching DEM has a minor(-)'s value, it can access that produce by high point than plot-map DEM.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.99-102
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• 2009

In this paper a hierarchical stereo matching algorithm based on feature extraction is proposed. The boundary (edge) as feature point in an image is first obtained by segmenting an image into red, green, blue and white regions. With the obtained boundary information, disparities are extracted by matching window on the image boundary, and the initial disparity map is generated when assigned the same disparity to neighbor pixels. The final disparity map is created with the initial disparity. The regions with the same initial disparity are classified into the regions with the same color and we search the disparity again in each region with the same color by changing block size and search range. The experiment results are evaluated on the Middlebury data set and it show that the proposed algorithm performed better than a phase based algorithm in the sense that only about 14% of the disparities for the entire image are inaccurate in the final disparity map. Furthermore, it was verified that the boundary of each region with the same disparity was clearly distinguished.