• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.4
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• pp.327-334
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• 2006

The aerial photos need in a simple object such as cartography and ground cover classification and also in a social objects such as the city plan, environment, disaster, transportation etc. However, the shadow, which includes when taking the aerial photos, makes a trouble to interpret the ground information, and also users, who need the photos in their field tasks, have a restriction. Generally the shadow occurs by the building and surface topography, and the detail cause is by changing of the illumination in an area. For removing the shadow this study uses the single image and processes the image without the source of image and taking situation. Also, applying the entropy minimization method it generates the 1-D gray-scale invariant image for creating the shadow edge mask and using the Canny edge detection creates the shadow edge mask, and finally by filtering in Fourier frequency domain creates the intrinsic image which recovers the 3-D color information and removes the shadow.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.61-68
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• 2004

In this paper, we suggest an automatic technique to obtain 3-D road information in complex urban areas using road pavement markings. This method is composed of following three main steps. The first step is extracting the pavement markings from aerial images, the second one is matching the same pavement markings in two aerial images, and the last one is obtaining the 3-D coordinates of those using EOP(exterior orientation parameters) of aerial images. Here, we focus on the first and second step because the last step can be performed by using the well hewn collinearity condition equation. We used geometric properties and spatial relationships of the pavement markings to extract the lane line markings on the images and extracted arrow lane markings additionally using template matching. And then, we obtained 3-D coordinates of the road using relational matching for the pavement markings. In order to evaluate the accuracy of extraction, we did a visual inspection and compared the result of this technique with those measured by digital photogrammetric system.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.187-190
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• 2007

This study is for analyzing best band in image matching using correlation coefficient of left and right images of stereo image pair, lot red, green, blue band images separated from color aerial photo and gray image converted from the same color aerial photo image. The image matching is applied to construct Digital Elevation Model(DEM) or terrain data. The correlation coefficients and variation by change of pixel patch size are computed from pixel patches of which sizes are $11{\times}11{\sim}101{\times}101$. Consequently, the correlation coefficient in red band image is highest. The lowest is in blue band. Therefore, to construct terrain data using image matching, the red band image is preferable. As the size of pixel patch is growing, the correlation coefficient is increasing. But increasing rate declines from $51{\times}51$ image patch size and above. It is proved that the smaller pixel patch size than $51{\times}51$ is applied to construct terrain data using image matching.

• Proceedings of the KSRS Conference
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• v.2
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• pp.899-902
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• 2006

For a quick and accurate 3D modelling of a building, laser scanning data, digital maps, aerial photographs and satellite images should be fusioned. Moreover, library establishment according to a standard structure of a building and effective texturing method are required in order to determine the structure of a building. In this study, we made a standard library by categorizing Korean village forms and presented a model that can predict a structure of a building from a shape of the roof on an aerial photo image. We made an ortho image using the high-definition digital image and considerable amount of ground scanning point cloud and mapped this image. These methods enabled a more quick and accurate building modelling.

• 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.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.773-775
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• 2003

From the view point of data fusion, we integrate LIDAR data and digital aerial images to perform 3D building modeling in this study. The proposed scheme comprises two major parts: (1) building block extraction and (2) building model reconstruction. In the first step, height differences are analyzed to detect the above ground areas. Color analysis is then performed for the exclusion of tree areas. Potential building blocks are selected first followed by the refinement of building areas. In the second step, through edge detection and extracting the height information from LIDAR data, accurate 3D edges in object space is calculated. The accurate 3D edges are combined with the already developed SMS method for building modeling. LIDAR data acquired by Leica ALS 40 in Hsin-Chu Science-based Industrial Park of north Taiwan will be used in the test.

• Journal of the Korean Institute of Rural Architecture
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• v.23 no.4
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• pp.1-12
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• 2021

Recently, the use of unmanned aerial vehicles (UAVs) is increasing in the field of land information acquisition and terrain exploration through high-altitude aerial photography. High-altitude aerial photography is suitable for large-scale geographic information collection, but has the disadvantage that it is difficult to accurately collect small-scale geographic information. Therefore, this study used low-altitude UAV to monitor changes in small rural spaces around rural resources, and the results are as follows. First, the low-altitude aerial imagery had a very high spatial resolution, so it was effective in reading and analyzing topographic features. Second, an area with a large number of aerial images and a complex topography had a large amount of point clouds to be extracted, and the number of point clouds affects the three-dimensional quality of rural space. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. In this study, the possibility of rural space analysis of low-altitude UAV was verified through aerial photography and analysis, and the effect of 3D mapping on rural space monitoring was visually analyzed. If data acquired by low-altitude UAV are used in various forms such as GIS analysis and topographic map production it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.372-378
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• 2016

The purpose of this study is to develop a system configuration for gathering data and building a database for agriculture. Some foreign agriculture-related companies have already constructed such a database for scientific agriculture. The hardware of this system is composed of automatic capturing equipment based on aerial photography using a UAV. The software is composed of parts for stitching images, matching GPS data with captured images, and building a database of collected weather information, farm operation data, and aerial images. We suggest a method for building the database, which can include information about the amount of agricultural products, weather, farm operation, and agricultural land images. The images of this system are about 5 times better than satellite images. Factors such as farm working and environmental factors can be basic data for analyzing the full impact of agriculture land. This system is expected to contribute to the scientific analysis of Korea's agriculture.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.825-828
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• 1991

This paper addresses estimation of the relative shift vector from aerial image sequences. We perform similarity function tests and decide the most appropriate similarity function for the visual navigation system using aerial images. Finally, we propose the maximum variance reference line selection method for reducing the estimation error of the shift vector.

• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.351-366
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• 2014

The aim of this study was to develop software for beach litter detection that includes a Graphical User Interface (GUI) and uses images taken by a micro-unmanned aerial vehicle. Videos were taken over Doomo pebble beach, Sogye pebble beach, and Heungnam sand beach on the northeast coast of Geojedo (Geoje Island), Korea. Still images of actual beach litter were obtained from the videos. The image processing involved preprocessing, morphological image processing, and image recognition. Comparison with still images showing beach litter demonstrated that the software could generally detect litter larger than 50 cm in size such as Styrofoam buoys and circular fish traps (excluding small pixel-size ropes). Combining the proposed method with the conventional surveying approach is expected to enhance the accuracy of beach litter detection. The new technique will also aid in predicting the amount of beach litter generated along coastlines, which is currently difficult to monitor.