• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.163-174
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• 2004

The 3D tooth model in which each tooth can be manipulated individualy is essential component for the orthodontic simulation and implant simulation in dental field. For the reconstruction of such a tooth model, we need an image segmentation algorithm capable of separating individual tooth from neighboring teeth and alveolar bone. In this paper we propose a CT image normalization method and adaptive optimal thresholding algorithm for the segmenation of tooth region in CT image slices. The proposed segmentation algorithm is based on the fact that the shape and intensity of tooth change gradually among CT image slices. It generates temporary boundary of a tooth by using the threshold value estimated in the previous imge slice, and compute histograms for the inner region and the outer region seperated by the temporary boundary. The optimal threshold value generating the finnal tooth region is computed based on these two histogram.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.166-174
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• 2006

In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Being based on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, stereo tracking of the target object can be possible. From some experiments with the 2 frames of the stereo image pairs having 256$\times$256 pixels, it is shown that the proposed stereo tracking system can adaptively track the target object with a low error ratio of about 3.05$\%$ on average between the detected and actual location coordinates of the target object.

• 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.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.6
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• pp.354-362
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• 2006

This paper suggests a method for generating high qualify stereo video avatar to support visual communication in a CAVE$^{TM}$-like system. In such a system because of frequent change of light projected onto screens around user, it is not easy to extract user silhouette robustly, which is an essential step to generate a video avatar. In this study, we use an infrared reflective image acquired by a grayscale camera with a longpass filter so that the change of visible light on a screen is blocked to extract robust user silhouette. In addition, using two color cameras positioned at a distance of a binocular disparity of human eyes, we acquire two stereo images of the user for fast generation and stereoscopic display of a high quality video avatar without 3D reconstruction. We also suggest a fitting algorithm of a silhouette mask on an infrared reflective image into an acquired color image to remove background. Generated stereo images of a video avatar are texture mapped into a plane in virtual world and can be displayed in stereoscopic using frame sequential stereo method. Suggested method have advantages that it generates high quality video avatar taster than 3D approach and it gives stereoscopic feeling to a user 2D based approach can not provide.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.109-118
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• 2006

In this paper, we suggest the environment based disparity method that calculate the depth value of the objects from environment maps. This method using the disparity of the environment map can calculate the depth value from two environment map that acquire at different viewpoint. This method can decide the visibility of the object whether it is occluded others or not. Also, we can analogize the depth value of the object that does not relate the reference plane(in case of being in the air) and make three dimensional environment model using the proposed method

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.77-77
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• 2000

The shape of small or curved object is usually reconstructed using a single camera by moving its lens position to find a sequence of the focused images. Most conventional methods have used a window with fixed shape to test the focus measure, which resulted in a deterioration of accuracy. To solve this problem, this paper proposes a new approach of using a shape adaptive window. It estimates the shape of the object at every step and applies the same shape of window to calculate the focus measure. Focus measure is based on the variance of the pixels inside the window. This paper includes the experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.4
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• pp.174-182
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• 2003

Recently, medical imaging has taken interest on CAD based solution for anatomical part fabrication or finite element analysis of human body. In principle, contours representing object boundary are obtained through image processing techniques. Surface models are then approximated by a skinning method. For this, various methods should be applied to medical images and contours. The major bottleneck of the reconstruction is to remove shape inconsistency between contours and to generate the branching surface. In order to solve these problems, bi-directional smoothing and the composite contour generation method are proposed. Bi-directional smoothing has advantage of removing the shape inconsistency between contours and minimizing shrinkage effect with a large number of iterations. The composite contour by the proposed method ensures smooth transition in branching region.

• Current Optics and Photonics
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• v.3 no.5
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• pp.451-457
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• 2019

Laser processing using holograms can greatly improve processing speed, by spatially distributing the laser energy on the target material. However, it is difficult to reconstruct an image with arrays of closely spaced spots for laser processing, because the specklelike interference pattern prevents the spots from getting close to each other. To resolve this problem, a line target was divided in two, reconstructed with orthogonally polarized beams, and then superposed. Their optical reconstruction was performed by computer-generated holograms and a pulsed laser. With this method, we performed two-dimensional (2D) laser drilling of polyimide film, with a kerf width of $20{\mu}m$ and a total processing length of 20 mm.

• Journal of IKEEE
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• v.7 no.1 s.12
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• pp.119-126
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• 2003

This paper presents a methodology for constructing a surgical simulation environment for the replacement of artificial knee join using CT image data. We provide a user interface of preoperative planning system for performing complex 3-D spatial manipulation and reasoning tasks. Simple manipulation of joystick and mouse has been proved to be both intuitive and accurate for the fitness and the wear expect of joint. The proposed methodology are useful for future virtual medical system where all the components of visualization, automated model generation, and surgical simulation are integrated.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.780-788
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• 2008

Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.