• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.80-89
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• 2008

Mapping applications using satellite imagery have been possible to quantitative analysis since SPOT satellite with stereo image was launched. Especially, high resolution satellite imagery was efficiently used in the field of digital mapping for the areas which are difficult to produce large-scale maps by aerial photogrammetry or carry out ground control point surveying due to unaccessibility. This study extracted the geospatial information out of consideration for topographic characteristic from ortho imagery of the National Geospatial-intelligence Agency(NGA) in the United States of America and analyzed the accuracy of plane coordinate for ortho imagery. For this purpose, the accuracy according to topographic character by comparison between both extraction data from ortho imagery and the digital topographic maps of 1:5000 scale which were produced by Korea National Geographic Information Institute(NGI) was evaluated. It is expected that the results of this study will be fully used as basic information for ground control point acquisition or digital mapping in unaccessible area.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.211-217
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• 2012

Conventional GrabCut algorithm is semi-automatic algorithm that user must be set rectangle window surrounds the object. This paper studied automatic object detection to solve these problem by detecting salient region based on Human Visual System. Saliency map is computed using Lab color space which is based on color opposing theory of 'red-green' and 'blue-yellow'. Then Saliency Points are computed from the boundaries of Low-Frequency region that are extracted from Saliency Map. Finally, Rectangle windows are obtained from coordinate value of Saliency Points and these windows are used in GrabCut algorithm to extract objects. Through various experiments, the proposed algorithm computing rectangle windows of salient region and extracting objects has been proved.

• Journal of KIISE
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• v.44 no.4
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• pp.392-398
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• 2017

The point-cloud representation of an object is performed by scanning a space through a laser scanner that is extracting a set of points, and the points are then integrated into the same coordinate system through a registration. The set of the completed registration-integrated point clouds is classified into meaningful regions, shapes, and noises through a mathematical analysis. In this paper, the aim is the matching of a curved area like a cylinder shape in 3D point-cloud data. The matching procedure is the attainment of the center and radius data through the extraction of the cylinder-shape candidates from the sphere that is fitted through the RANdom Sample Consensus (RANSAC) in the point cloud, and completion requires the matching of the curved region with the Catmull-Rom spline from the extracted center-point data using the Principal Component Analysis (PCA). Not only is the proposed method expected to derive a fast estimation result via linear and curved cylinder estimations after a center-axis estimation without constraint and segmentation, but it should also increase the work efficiency of reverse engineering.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.220-223
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• 2004

Automatic image registration is an essential element of remote sensing because remote sensing system generates enormous amount of data, which are multiple observations of the same features at different times and by different sensor. The general process of automatic image registration includes three steps: 1) The extraction of features to be used in the matching process, 2) the feature matching strategy and accurate matching process, 3) the resampling of the data based on the correspondence computed from matched feature. For step 2) and 3), we have developed an algorithms for automated registration of satellite images with RANSAC(Random Sample Consensus) in success. However, for step 1), There still remains human operation to generate GCP Chips, which is time consuming, laborious and expensive process. The main idea of this research is that we are able to automatically generate GCP chips with comer detection algorithms without GPS survey and human interventions if we have systematic corrected satellite image within adaptable positional accuracy. In this research, we use SUSAN(Smallest Univalue Segment Assimilating Nucleus) algorithm in order to detect the comer. SUSAN algorithm is known as the best robust algorithms for comer detection in the field of compute vision. However, there are so many comers in high-resolution images so that we need to reduce the comer points from SUSAN algorithms to overcome redundancy. In experiment, we automatically generate GCP chips from IKONOS images with geo level using SUSAN algorithms. Then we extract reference coordinate from IKONOS images and DEM data and filter the comer points using texture analysis. At last, we apply automatically collected GCP chips by proposed method and the GCP by operator to in-house automatic precision correction algorithms. The compared result will be presented to show the GCP quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.444-450
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• 1999

This paper deals with several methods: the clustering method that uses k-means algorithm to abstract the area of characters on the image document and the distance function that suits for the HIS coordinate system to cluster the image. For the prepossessing step to recognize this, or the method of characters segmentate, the algorithm to abstract a discrete character is also proposed, using the linking picture element. This algorithm provides the feature that separates any character such as the touching or overlapped character. The methods of projecting and tracking the edge have so far been used to segment them. However, with the new method proposed here, the picture element extracts a discrete character with only one-time projection after abstracting the character string. it is possible to pull out it. dividing the area into the character and the rest (non-character). This has great significance in terms of processing color documents, not the simple binary image, and already received verification that it is more advanced than the previous document processing system.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.47-56
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• 1999

In this study, tie point observation in aerial triangulation was automated by the image processing methods. The technique includes boundary extraction and We matching processes. The procedures were applied to extract points of Interest and to find their conjugate points in the other images. The image coordinates of the identified points were then used to compute their absolute coordinates. An algorithm was developed in this study for the automation of observation in aerial triangulation, which is a manual process of selecting a tie point and recording the image coordinate of the selected point. The developed algorithm automates this process through the application of a mathematical operator to extract points of interest from an arbitrary image. The root m square error of image coordinates of the developed algorithm is $6.8{\mu}m$, which is close to that of the present analytical method. In a manual environment, the accuracy of the result of a photogrammetric process is heavily dependant on the level of skill and experience of the human operator. No such problem exists in an automated system. Also, as a result of the automated system, the time spent in the observation process could be reduced by a factor of 61.2%, thereby reducing the overall cost.

• Applied Chemistry for Engineering
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• v.27 no.3
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• pp.325-329
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• 2016

Extracting natural dyes have been widely studied since the needs of eco-friendly and non-toxic natural dyes increased. In this paper, the natural dyes were extracted from sappan wood, gardenia, and mugwort containing brazilein, crocin, and chlorophyll process. After the extraction with variables of pH of solvent and reaction time, the chromaticity of extracted natural dyes was analyzed using quantitative values from brightness and color coordinate (L, a, b) based on the target colors of red, yellow and green. For the case of brazilein and crocin, the cadmium red and cadmium yellow, respectively were extracted. In the case of sappan wood and gardenia, the red pigment under pH 12 (${\Delta}$ = 18.2) and the yellow pigment at pH 9 (${\Delta}$ = 18.4) were extracted respectively. However, the color of extracted chlorophyll from mugwort was different from the target chrome green.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.217-226
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• 2006

Extraction and tracking objects are fundamental and important steps of the digital image processing and computer vision. Many algorithms about extracting and tracking objects have been developed. In this research, a method is suggested for tracking a moving object using a pair of CCD cameras and calculating the coordinate of the moving object. A 1/100 miniature of soccer field was made to apply the developed algorithms. After candidates were selected from the acquired images using the RGB value of a moving object (soccer ball), the object was extracted using its size (MBR size) among the candidates. And then, image coordinates of a moving object are obtained. The real-time position of a moving object is tracked in the boundary of the expected motion, which is determined by centering the moving object. The 3D position of a moving object can be obtained by conducting the relative orientation, absolute orientation, and space intersection of a pair of the CCD camera image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.1007-1016
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• 2005

This paper presents a feature extraction method for shape based retrieval of 3D models. Since the feature descriptor of 3D model should be invariant to translation, rotation and scaling, it is necessary to preprocess the 3D models to represent them in a canonical coordinate system. We use the PCA(Principal Component Analysis) method to preprocess the 3D models. Also, we apply that to make a MBR(Minimum Boundary Rectangle) and a circumsphere. The proposed algorithm is as follows. We generate a circumsphere around 3D models, where radius equals 1(r=1) and locate each model in the center of the circumsphere. We produce the concentric spheres with a different radius($r_i=i/n,\;i=1,2,{\ldots},n$). After looking for meshes intersected with the concentric spheres, we compute the curvature of the meshes. We use these curvatures as the model descriptor. Experimental results numerically show the performance improvement of proposed algorithm from min. 0.1 to max. 0.6 in comparison with conventional methods by ANMRR, although our method uses .relatively small bins. This paper uses $R{^*}-tree$ as the indexing.

• Journal of Korean Dental Science
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• v.7 no.2
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• pp.66-79
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• 2014

Purpose: To analyze the amount and pattern of tooth movement and the changes in arch dimension of mandibular dentition after orthodontic treatment using a new three-dimensional (3D)-indirect superimposition method. Materials and Methods: The samples consisted of fifteen adult patients with class I bialveolar protrusion and minimal anterior crowding, treated by extraction of four first premolars with conventional sliding mechanics. After superimposition of 3D-virtual maxillary models before and after treatment using best-fit method, 3D-virtual mandibular model at each stage was placed into a common coordinate of superimposition using 3D-bite information, which resulted in 3D-indirect superimposition for mandibular dentition. The changes in mandibular dental and arch dimensional variables were measured with Rapidform 2006 (INUS Technology). Paired t-test was used for statistical analysis. Result: The anterior teeth moved backward, displaced laterally, and inclined lingually. The posterior teeth showed statistically significant contraction toward midsagittal plane. The amounts of backward movement of anterior teeth and forward movement of posterior teeth showed a ratio of 6 : 1. Although the inter-canine width increased slightly (0.8 mm, P<0.05), the inter-second premolar, inter-first molar, and inter-second molar widths decreased significantly with similar amounts (2.2 mm, P<0.05; 2.3 mm, P<0.01; 2.3 mm, P<0.001). The molar depth decreased (6.7 mm, P<0.001) but canine depth did not change. Conclusion: A new 3D-indirect superimposition of the mandibular dentitions using best-fit method and 3D-bite information can present a guideline for virtual treatment planning in terms of tooth position and arch dimension.