• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2009.04a
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• pp.129-132
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• 2009

Automatic target recognition surveying method is very important technology one-man surveying system. But in the case of loss of prism's position, it have to be re-tracking for searching it, consuming the searching time and complicated in processing. In this study, it is proposed new GPS receiver combination technology for orientation of both. In conclusion, the robotic TS(totalstation) is well assisted by absolute coordinates from single GPS receiver and multi-functional surveying instrument.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.157-160
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• 2010

Terrestrial LiDAR data contains outliers which do not need in processing purpose. That is inefficient in the aspect of productivity. These noise requires manual process to be removed, which causes inefficiency in aspect of productivity. The purpose of this research is to demonstrate a possibility of automatic outlier removal of LiDAR data using 3D Tensor Voting method. For this, we presented in this article about the procedure to perform the application of Tensor Voting algorithm to the real data from terrestrial LiDAR.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.2 no.1
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• pp.46-53
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• 1984

This paper deals with the practical application in the way how the automatic contouring can be done by DTM, the results of investigation confirm that the digital contouring is equivalent to results from direct photogrammetric contouring. The data acquisition is restericted in 841$(29{\times}29)$ regular grid points, the interpolation is done by concepts of finite elements. finally, the output map is relatively compare with A-10 contour maps.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.02a
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• pp.38-44
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• 2004

NASA, NSF and USGS jointly conducted LIDAR surveys to acquire numerous surface points with high densities over the Antarctic Dry Valleys and its vicinity. The huge set of the points unusually includes many blunders, retaining large variation of the point densities. Hence, to reduce the undesirable effects due to these characteristics and process the huge number of points with reasonable time and resources, we developed an efficient, robust, nearly automatic approach to DEM generation. This paper reports about the application of this approach to generating high-resolution precise DEMs from the Antarctic LIDAR surveys and the evaluation of their accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.91-97
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• 2019

In automatic map generalization, the formalization of cartographic principles is important. This study proposes and evaluates the selection method for road network generalization that analyzes existing maps using reverse engineering and formalizes the selection rules for the road network. Existing maps with a 1:5,000 scale and a 1:25,000 scale are compared, and the criteria for selection of the road network data and the relative importance of each network object are determined and analyzed using $T{\ddot{o}}pfer^{\prime}s$ Radical Law as well as the logistic regression model. The selection model derived from the analysis result is applied to the test data, and road network data for the 1:25,000 scale map are generated from the digital topographic map on a 1:5,000 scale. The selected road network is compared with the existing road network data on the 1:25,000 scale for a qualitative and quantitative evaluation. The result indicates that more than 80% of road objects are matched to existing data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.59-65
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• 2012

In this paper, we proposed a method for automatic detection of a updating object from spatial data sets of different scale and updating cycle by using areal feature matching based on shape similarity. For this, we defined a updating object by analysing matching relationships between two different spatial data sets. Next, we firstly eliminated systematic errors in different scale by using affine transformation. Secondly, if any object is overlaid with several areal features of other data sets, we changed several areal features into a single areal feature. Finally, we detected the updating objects by applying areal feature matching based on shape similarity into the changed spatial data sets. After applying the proposed method into digital topographic map and a base map of Korean Address Information System in South Korea, we confirmed that F-measure is highly 0.958 in a statistical evaluation and that significant updating objects are detected from a visual evaluation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.1-10
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• 2012

Recent spatial information technology has brought innovative improvement in both efficiency and accuracy. Especially, airborne LiDAR system(ALS) is one of the practical sensors to obtain 3D spatial information. Constructing reliable 3D spatial data infrastructure is world wide issue and most of the significant tasks involved with modeling manmade objects. This study aims to create a test data set for developing automatic building modeling methods by simulating point cloud data. The data simulates various roof types including gable, pyramid, dome, and combined polyhedron shapes. In this study, a robust bottom-up method to segment surface patches was proposed for generating building models automatically by determining model key points of the objects. The results show that building roofs composed of the segmented patches could be modeled by appropriate mathematical functions and the model key points. Thus, 3D digitizing man made objects could be automated for digital mapping purpose.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.2
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• pp.131-140
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• 2020

Recently the importance of BIM (Building Information Modeling) that enables 3D location-based design and construction work is being highlighted around the world. In Korea, the road map has been established to settle the design based on BIM using drone survey results by 2025. As the first step, BIM would be applied to road construction projects worth more than 50 billion Korean Won from 2020. On the other hand, drone survey regulation has been enacted and the data for drone survey cost were also included on Standard of construction estimate in 2020. However, more careful improvement is required to reflect drone survey results in BIM design and construction. Currently, Engineering instructions and Standard of construction estimate specifies that earthwork volume must be calculated by cross section method only. So it is required to add the method of DEM (Digital Elevation Model) based volume calculation on these regulations to realize BIM application. In order for that, this study verified the method of DEM based earthwork volume calculation. To get an accurate DEM for accurate volume computation, drone survey was carried out according to the drone survey regulation and then could get an accurate DEM data which have errors less than 3cm in X, Y and 6.8cm in H. As each DEM cell has 3D coordinate component, the volume of each cell can be calculated by obtaining the height of area of the cell then total volume is calculated by multiplying total number of cells by volume of each cell for the construction area. Verification for the new calculation method compare with existing method was carried out. The difference between DEM based volume by drone survey and cross section based volume by traditional survey was less than 1.33% and it can be seen that new DEM method will be able to be applied to BIM design and construction instead of cross section method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.627-636
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• 2010

Image segmentation technique is becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification to extract object regions of interest within images. This paper presents a new method for image segmentation to consider spectral and spatial information of high resolution satellite image. Firstly, the initial seeds were automatically selected using local variation of multi-spectral edge information. After automatic selection of significant seeds, a segmentation was achieved by applying MSRG which determines the priority of region growing using information drawn from similarity between the extracted each seed and its neighboring points. In order to evaluate the performance of the proposed method, the results obtained using the proposed method were compared with the results obtained using conventional region growing and watershed method. The quantitative comparison was done using the unsupervised objective evaluation method and the object-based classification result. Experimental results demonstrated that the proposed method has good potential for application in the object-based analysis of high resolution satellite images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.595-603
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• 2015

With the advances of the big-data process technology, acquiring the real-time information from the massive image data taken by a mobile device inside a vehicle will be possible in the near future. Among the information that can be found around the vehicle, the route information is needed for safe driving. In this study, the automatic extraction of route information from the road sign imagery was dealt with. The scope of the route information in this study included the route number, route type, and their relationship with the driving direction. For the recognition of the route number, the modified Tesseract OCR (Optical Character Recognition) engine was used after extracting the rectangular-road-sign area with the Freeman chain code tracing algorithm. The route types (expressway, highway, rural highway, and municipal road) are recognized using the proposed algorithms, which are acquired from colour space analysis. Those road signs provide information about the route number as well as the roads that may be encountered along the way. In this study, such information was called “OTW (on the way)” or “TTW (to the way)” which between the two should be indicated is determined using direction information. Finally, the route number is matched with the direction information. Experiments are carried out with the road sign imagery taken inside a car. As a result, route numbers, route number type, OTW or TTW are successfully recognized, however some errors occurred in the process of matching TTW number with the direction.