• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.509-514
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• 2003

The virtual bronchoscopy was implemented using chest CT images to visualize inside of tracheo-bronchial wall. The optical endoscopy procedures are invasive, uncomfortable for patients and sedation or anesthesia may be required. Also, they have serious side effects such as perforation, infection and hemorrhage. In order to determine the navigation path, we segmented the tracheo-bronchial wall from the chest CT image. We used the coordinates as a navigation path for virtual camera that were calculated from medial axis transformation. We used the perspective projection and marching cube algorithm to render the surface from volumetric CT image data. The tracheobronchial disease was classified into tracheobronchial stenosis causing from inflammation or lung cancer, bronchiectasis and bronchial cancer. The virtual bronchoscopy is highly recommended as a diagnosis tool with which the specific place of tracheobronchial disease can be identified and the degree of tracheobronchial disease can be measured qualitatively, Also, the virtual bronchoscopy can be used as an education and training tool for endoscopist and radiologist.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.27-37
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• 2004

The detection of foreground objects in a projection display using color information can be hard due to changing lighting conditions and complex backgrounds. Accordingly, the current paper proposes a foreground object detection method using color information that is obtained from the input image to the Projector and an image captured by a camera above the projection display. After pixel correspondences between the two images are found by calibrating the geometry distortion and color distortion, the natural color variations are estimated for the projection display. Then, any pixel that has another variation not resulting from natural geometry or color distortion is considered a part of foreground objects, because a foreground object in a projection display changes the values of pixels. As shown by experimental results, the proposed foreground detection method is applicable to an interactive projection display system such as the DigitalDesk

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.207-213
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• 2018

This paper investigates applicability of Microsoft $Kinect^{(R)}$, RGB-depth camera, to implement a 3D image and spatial information for sensing a target. The relationship between the image of the Kinect camera and the pixel coordinate system is formulated. The calibration of the camera provides the depth and RGB information of the target. The intrinsic parameters are calculated through a checker board experiment and focal length, principal point, and distortion coefficient are obtained. The extrinsic parameters regarding the relationship between the two Kinect cameras consist of rotational matrix and translational vector. The spatial images of 2D projection space are converted to a 3D images, resulting on spatial information on the basis of the depth and RGB information. The measurement is verified through comparison with the length and location of the 2D images of the target structure.

• Fire Science and Engineering
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• v.31 no.4
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• pp.20-25
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• 2017

In the present study, the temperature distribution of droplet diffusion flames was predicted from the measurements of radiative emissions of soot particles formed. In order to predict the temperature distributions, the radiative emissions from soot particles filtered at both 700 nm and 900 nm were measured using CCD cameras and local emission distributions within the flame deconvoluted with Abel transformation were plugged into a two color method. The experimental results obtained from the present study demonstrate that the two color method as tool for temperature measurements is feasible but can introduce approximately 2% maturement errors in a deconvolution process depending on intervals for the line of sight. The estimated error in temperature measurements was found to be within 18 K at 2000 K.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1341-1347
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• 2007

The displacement field (Optical flow) has been calculated by bottom-up approaches based on local processing. In contrast with them, in this paper, a top-down approach based on expanding in turn from the lowest order mode the whole motion in an image pair of sequential images is proposed. The intensity of medical images usually represents a quantity which is conserved during the motion. Hence sequential images are ideally related by a coordinate transformation. The displacement field can be determined from the generalized moments of the two images. The equations which transform arbitrary generalized moments from a source image to a target image are expressed as a function of the displacement field. The appareent displacement field is then computed iteratively by a projection method which utilizes the functional derivatives of the linearized moment equations. This method is demonstrated using a pair of sequential heart images. For comparative evaluation, we applied Horn and Schunck's method, a standard multigrid method, and our proposed algorithm to sequential image.

• Korean Journal of Remote Sensing
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• v.8 no.2
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• pp.93-104
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• 1992

Although the Transverse Mercator(TM) coordinate is used on standard topogrphic maps of Korea as a supplement to regular latitude-longitude coordinate, the use of this TM coordinate system is rather limited to a single coordinate zone that spans only two degrees of longitude. With growing applications of a variety of digiral geographic data, such as satellite remote sensor data, a Cartesian or rectangular coordinate system is more effective to deal with such data type than angular coordinate system. An unified rectangular coordinate system based on the Transverse Mercator projection is designed to cover the whole area of the Korea Peninsula as a single coordinate zone. Considering the width of the peninsula and the distribution of scale error, the origin of the coordinate is determined to 127$^{\circ}$30' east and 38$^{\circ}$ north. Coordinate conversion procedure is discussed along with the corresponding scale error term.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.293-296
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• 2016

In case of an emergency on a busy road of a city, drivers should make way for special vehicles such as police cars, fire engines, or ambulance as soon as possible. If road infrastructures recognize the movements of special vehicles, and transfer alert message to traffic signal controllers and normal cars through wireless network such as WAVE or TPEG, normal cars can prepare to make way in advance. As a result, it help special vehicles move faster. In this paper, we install a roof mark on the roof of a special vehicle, detect the mark through a mark recognition algorithm which includes perspective transformation, and get the inner information by decoding the digital pattern on it. The experiment results show that mark can be recognized 100% and 93.3% of inner digital data of the mark can be recognized, when the size of a mark is larger than $88cm{\times}88cm$ and the mark moves at a speed of 50km/s.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.89-96
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• 2019

360 degree 3-dimensional lidar sensors and vision cameras are commonly used in the development of autonomous driving techniques for automobile, drone, etc. By the way, existing calibration techniques for obtaining th e external transformation of the lidar and the camera sensors have disadvantages in that special calibration objects are used or the object size is too large. In this paper, we introduce a simple calibration method between two sensors using a spherical object. We calculated the sphere center coordinates using four 3-D points selected by RANSAC of the range data of the sphere. The 2-dimensional coordinates of the object center in the camera image are also detected to calibrate the two sensors. Even when the range data is acquired from various angles, the image of the spherical object always maintains a circular shape. The proposed method results in about 2 pixel reprojection error, and the performance of the proposed technique is analyzed by comparing with the existing methods.

• The Journal of Information Technology
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• v.7 no.2
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• pp.93-104
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• 2004

Sports scene is characterized by large amount of global motion due to pan and zoom of camera motion, and includes many small objects moving independently. Some short period of sports games is thrilling to televiewers, and important to producers. At the same time that kinds of scenes exhibit exceptionally dynamic motions and it is very difficult to analyze the motions with conventional algorithms. In this thesis, several algorithms are proposed for global motion analysis on these dynamic scenes. It is shown that proposed algorithms worked well for motion compensation and panorama synthesis. When cascading the inter frame motions, accumulated errors are unavoidable. In order to minimize these errors, interpolation method of motion vectors is introduced. Affined transform or perspective projection transform is regarded as a square matrix, which can be factorized into small amount of motion vectors. To solve factorization problem, we preposed the adaptation of Newton Raphson method into vector and matrix form, which is also computationally efficient. Combining multi frame motion estimation and the corresponding interpolation in hierarchical manner enhancement algorithm of motion parameters is proposed, which is suitable for motion compensation and panorama synthesis. The proposed algorithms are suitable for special effect rendering for broadcast system, video indexing, tracking in complex scenes, and other fields requiring global motion estimation.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.493-502
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• 2007

An on-line registration technique is presented to register multi-view range images for the 3D reconstruction of real objects. Using a range camera, we first acquire range images and photometric images continuously. In the range images, we divide object and background regions using a predefined threshold value. For the coarse registration of the range images, the centroid of the images are used. After refining the registration of range images using a projection-based technique, we use a modified KLT(Kanade-Lucas-Tomasi) tracker to match photometric features in the object images. Using the modified KLT tracker, we can track image features fast and accurately. If a range image fails to register, we acquire new range images and try to register them continuously until the registration process resumes. After enough range images are registered, they are integrated into a 3D model in offline step. Experimental results and error analysis show that the proposed method can be used to reconstruct 3D model very fast and accurately.