• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1464-1466
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• 2003

classification of the satellite images provides information about land cover and/or land use. Quality of the classification result depends mainly on the spatial and spectral resolutions of the images. In this study, image fusion in terms of resolution merging, and band integration with multi-source of the satellite images; Landsat ETM+ and Ikonos were carried out to improve classification. Resolution merging and band integration could generate imagery of high resolution with more spectral bands. Precise image co-registration is required to remove geometric distortion between different sources of images. Combination of unsupervised and supervised classification of the fused imagery was implemented to improve classification. 3D display of the results was possible by combining DEM with the classification result so that interpretability could be improved.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.505-507
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• 2003

This paper describes techniques for the automated creation of geometric 3D models of the urban area us ing two 2D laser scanners and aerial images. One of the laser scanners scans an environment horizontally and the other scans vertically. Horizontal scanner is used for position estimation and vertical scanner is used for building 3D model. Aerial image is used for registration with scan data. Those models can be used for virtual reality, tele-presence, digital cinematography, and urban planning applications. Results are shown with 3D point cloud in urban area.

• International Journal of Highway Engineering
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• v.15 no.4
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• pp.177-186
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• 2013

PURPOSES: The purpose of this study theoretically reviews vertical grade deriving process in super high speed environment and compares overseas design criteria with Domestic Standardization also draws suitable vertical grade design criteria of high standard for Domestic Circumstances in Korea. METHODS : By researching domestic vehicle registration status, calculating typical vehicle, using Vissim which is traffic simulation program, Speed-distance curve of the vehicle is derived under each design speed condition. Through Speed-distance curve, estimating critical length of grade and considering critical length of grade, maximum longitudinal incline is proposed. RESULTS : The result of domestic vehicle registration status, the typical vehicle for deriving vertical grade is calculated based on gravity horsepower ratio 200 lb/hp. For calculating critical length of grade, according to change speed of uphill entry, speed-distance curve is derived by using Vissim. Critical length of grade is calculated based on design speed 20 km/h criteria which is point of retardation. Estimated critical length of grade is 808 m and based on this result, maximum longitudinal incline was confirmed in the design speed between 130km/h to 140km/h. CONCLUSIONS: The case of the typical vehicle(truck) which is gravity horsepower ratio 200 lb/hp, maximum longitudinal incline 2% is desirable at the super high speed environment in the design speed between 130km/h to 140km/h.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.49-56
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• 2009

Recently, a generation of high quality mosaic images from video sequences has been attempted by a variety of investigations. Among the matter of investigation, in this paper, generation on stereo mosaic utilizing airborne-video sequence images is focused upon. The stereo mosaic is made by creating left and right mosaic which are fabricated by front and rear slices having different viewing angle in consecutive video frames. For making the stereo mosaic, motion parameters which are able to define geometric relationship between consecutive video frames are determined. For determining motion parameters, affine model which is able to explain relative motion parameters is applied by this paper. The mosaicing method using relative motion parameters is called by free mosaic. The free mosaic proposed in this paper consists of 4 step processes: image registration with reference to first frame using affine model, front and rear slicing, stitching line definition and image mosaicing. As the result of experiment, the left and right mosaic image, anaglyphic image for stereo mosaic images are showed and analyzed y-parallax for checking accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.24-34
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• 2007

Application systems that easy to access a information have been developed by IT growth and a human life variation. In this paper, we propose a application system to register a 3D footwear model using a monocular camera. In General, a human motion analysis research to body movement. However, this system research a new method to use a foot movement. This paper present a system process and show experiment results. For projection to 2D foot plane from 3D shoe model data, we construct processes that a foot tracking, a projection expression and pose estimation process. This system divide from a 2D image analysis and a 3D pose estimation. First, for a foot tracking, we propose a method that find fixing point by a foot characteristic, and propose a geometric expression to relate 2D coordinate and 3D coordinate to use a monocular camera without a camera calibration. We make a application system, and measure distance error. Then, we confirmed a registration very well.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.258-268
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• 2021

Point cloud content is immersive content that represents real-world objects with three-dimensional (3D) points. In the process of acquiring point cloud data or encoding and decoding point cloud data, the resolution of point cloud content could be degraded. In this paper, we propose a method of progressively enhancing the resolution of sequential point cloud contents through inter-frame registration. To register a point cloud, the iterative closest point (ICP) algorithm is commonly used. Existing ICP algorithms can transform rigid bodies, but there is a disadvantage that transformation is not possible for non-rigid bodies having motion vectors in different directions locally, such as point cloud content. We overcome the limitations of the existing ICP-based method by registering regions with motion vectors in different directions locally between the point cloud content of the current frame and the previous frame. In this manner, the resolution of the point cloud content with geometric movement is enhanced through the process of registering points between frames. We provide four different point cloud content that has been enhanced with our method in the experiment.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.2393-2398
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• 2012

Objectives: The purpose of this study was to evaluate the geometric accuracy of thoracic anatomic landmarks as target surrogates of intrapulmonary tumors for manual rigid registration during image-guided radiotherapy (IGRT). Methods: Kilovolt cone-beam computed tomography (CBCT) images acquired during IGRT for 29 lung cancer patients with 33 tumors, including 16 central and 17 peripheral lesions, were analyzed. We selected the "vertebrae", "carina", and "large bronchi" as the candidate surrogates for central targets, and the "vertebrae", "carina", and "ribs" as the candidate surrogates for peripheral lesions. Three to six pairs of small identifiable markers were noted in the tumors for the planning CT and Day 1 CBCT. The accuracy of the candidate surrogates was evaluated by comparing the distances of the corresponding markers after manual rigid matching based on the "tumor" and a particular surrogate. Differences between the surrogates were assessed using 1-way analysis of variance and post hoc least-significant-difference tests. Results: For central targets, the residual errors increased in the following ascending order: "tumor", "bronchi", "carina", and "vertebrae"; there was a significant difference between "tumor" and "vertebrae" (p = 0.010). For peripheral diseases, the residual errors increased in the following ascending order: "tumor", "rib", "vertebrae", and "carina"; There was a significant difference between "tumor" and "carina" (p = 0.005). Conclusions: The "bronchi" and "carina" are the optimal surrogates for central lung targets, while "rib" and "vertebrae" are the optimal surrogates for peripheral lung targets for manual matching of online and planned tumors.

• Journal of radiological science and technology
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• v.35 no.2
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• pp.173-181
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• 2012

The aim of this study is to compare the geometric characteristics of the lung tumor, such as tumor centroid, HU change relative to breath phase, depending on tumor location and adhesion using 4DCT and deformable image registration program (MIMVista). The Y axis change was most significant and the mean Y axis centroid fluctuation was $7.32{\pm}6.88mm$ in lower lung tumor. The mean HU variation in lower lung mass has changed more than other locations, and its mean HU variation was $7.7{\pm}4.97%$ and non-adhered mass was more changed. Correlation for the mass volume between 3DCT and MIP was very high and its coefficient was 0.998. The effect of tumor location, adhesion and diaphragm excursion to geometric uncertainties was analyzed by linear regression model, it was influenced to mass deformation and geometrical variation so much except diaphragm excursion. but intra-fractional and inter-patient's uncertainties were great, so it couldn't find any exact deformation trend.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.3
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• pp.183-190
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• 2007

To make use of surveying data obtained from different sensors and different techniques, it is a pre-requite step that register them in a common coordinate system. For this purpose, we developed methodologies to register IKONOS-2 Satellite Imagery using LiDAR(Light Detection And Ranging) data. To achieve this, conjugate features from these data should be extracted in advance. In this study, linear features are chosen as conjugate features. Then, to register them, observation equations are established from similarity measurements of the extracted features and the results was evaluated statistically. The results clearly demonstrate that the proposed algorithms are appropriate to register these data.