• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.403-410
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• 2016

This paper proposes a robust image-based visual servoing scheme using a nonlinear observer for a monocular eye-in-hand manipulator. The proposed control method is divided into a range estimation phase and a target-tracking phase. In the range estimation phase, the range from the camera to the target is estimated under the non-moving target condition to solve the uncertainty of an interaction matrix. Then, in the target-tracking phase, the feature point uncertainty caused by the unknown motion of the target is estimated and feature point errors converge sufficiently near to zero through compensation for the feature point uncertainty.

• The Journal of the Korea Contents Association
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• v.3 no.2
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• pp.24-30
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• 2003

Pre-existing authentication system such as token based method, knowledge-based and hybrid method have problems such as loss and wiretapping. for this, this paper describes the biometric authentication system which have the excellent convenience and security. In particular, a new biometric system by human face biometric features which have the non-enforcement and non-touch measurement is proposed. Firstly, facial features are extracted by Y- histogram and tilted face images we corrected by coordinate transformation and scaling has done for achieving independent of the camera positions. Secondly, feature vectors are extracted such as distance and intersection angles and similarities we measured by fuzzy relation matrix. finally, the effectiveness of this paper is demonstrated by experiments.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.641-650
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• 2010

Color image sensors (CIS) output color images through image sensors and image signal processing. Image sensors that convert light to electrical signal are divided into CMOS image sensor and CCD image sensor according to transferring method of signal charge. In general, a CIS has RGB output signals from tri-stimulus XYZ of the scene through image signal processing. This paper presents an adaptive colorimetric analysis method to obtain chromaticity and luminance using CIS under various environments. An image sensor for the use of colorimeter is characterized based on the CIE standard colorimetric observer. We use the method of least squares to derive a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values. We first survey the camera characterization in the standard environment then derive a SGL(shutter-gain-level) function which is relationship between luminance and auto exposure (AE) characteristic of CIS, and read the status of an AWB(auto white balance) function. Then we can apply CIS to measure luminance and chromaticity from camera outputs and AE resister values without any preprocessing. Camera RGB outputs, register values, and camera photoelectric characteristic are used to analyze the colorimetric results for real scenes such as chromaticity and luminance. Experimental results show that the proposed method is valid in the measuring performance. The proposed method can apply to various fields like surveillant systems of the display or security systems.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.94-100
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• 2010

Purpose: We can evaluate function of kidney by Glomerular Filtration Rate (GFR) test using $^{99m}Tc$-DTPA which is simple. This test is influenced by several parameter such as net syringe count, kidney depth, corrected kidney count, acquisition time and characters of gamma camera. In this study, we evaluated predose count according to matrix size in the GFR test using $^{99m}Tc$-DTPA. Materials and Methods: Gamma camera of Infinia in GE was used, and LEGP collimator, three types of matrix size ($64{\times}64$, $128{\times}128$, $256{\times}256$) and 1.0 of zoom factor were applied. We increased radioactivity concentration from 222 (6), 296 (8), 370 (10), 444 (12) up to 518 MBq (14 mCi) respectively and acquired images according to matrix size at 30 cm distance from detector. Lastly, we evaluated these values and then substituted them for GFR formula. Results: In $64{\times}64$, $128{\times}128$ and $256{\times}256$ of matrix size, counts per second was 26.8, 34.5, 41.5, 49.1 and 55.3 kcps, 25.3, 33.4, 41.0, 48.4 and 54.3 kcps and 25.5, 33.7, 40.8, 48.1 and 54.7 kcps respectively. Total counts for 5 second were 134, 172, 208, 245 and 276 kcounts from $64{\times}64$, 127, 172, 205, 242, 271 kcounts from $128{\times}128$, and 137, 168, 204, 240 and 273 kcounts from $256{\times}256$, and total counts for 60 seconds were 1,503, 1,866, 2,093, 2,280, 2,321 kcounts, 1,511, 1,994, 2,453, 2,890 and 3,244 kcounts, and 1,524, 2,011, 2,439, 2,869 and 3,268 kcounts respectively. It is different from 0 to 30.02 % of percentage difference in $64{\times}64$ of matrix size. But in $128{\times}128$ and $256{\times}256$, it is showed 0.60 and 0.69 % of maximum value each. GFR of percentage difference in $64{\times}64$ represented 6.77% of 222 MBq (6 mCi), 42.89 % of 518 MBq (14 mCi) at 60 seconds respectively. However it is represented 0.60 and 0.63 % each in $128{\times}128$ and $256{\times}256$. Conclusion: There was no big difference in total counts of percentage difference and GFR values acquiring from $128{\times}128$ and $256{\times}256$ of matrix size. But in $64{\times}64$ of matrix size when the total count exceeded 1,500 kcounts, the overflow phenomenon was appeared differently according to predose radioactivity of concentration and acquisition time. Therefore, we must optimize matrix size and net syringe count considering the total count of predose to get accurate GFR results.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.89-96
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• 2015

Human visual system has chromatic adaptation to determine the color of an object regardless of illumination, whereas digital camera records illumination and reflectance together, giving the color appearance of the scene varied under different illumination. NMFsc(nonnegative matrix factorization with sparseness constraint) was recently introduced to estimate original object color by using sparseness constraint. In NMFsc, low sparseness constraint is used to estimate illumination and high sparseness constraint is used to estimate reflectance. However, NMFsc has an illumination estimation error for images with large uniform area, which is considered as dominant chromaticity. To overcome the defects of NMFsc, illumination estimation via nonnegative matrix factorization with dominant chromaticity image is proposed. First, image is converted to chromaticity color space and analyzed by chromaticity histogram. Chromaticity histogram segments the original image into similar chromaticity images. A segmented region with the lowest standard deviation is determined as dominant chromaticity region. Next, dominant chromaticity is removed in the original image. Then, illumination estimation using nonnegative matrix factorization is performed on the image without dominant chromaticity. To evaluate the proposed method, experimental results are analyzed by average angular error in the real world dataset and it has shown that the proposed method with 5.5 average angular error achieve better illuminant estimation over the previous method with 5.7 average angular error.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1178-1188
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• 2003

In this paper, we describe image mosaicing techniques for constructing a large high-resolution image with images taken by a video camera in hand. we propose the method which is automatically retrieving the exact matching area using color information and shape information. The proposed method extracts first candidate areas which have similar form using a Voronoi Distance Matching Method which is rapidly estimating the correspondent points between adjacent images, and calculating initial transformations of them and finds the final matching area using color information. It is a method that creates Voronoi Surface which set the distance value among feature points and other points on the basis of each feature point of a image, and extracts the correspondent points which minimize Voronoi Distance in matching area between an input image and a basic image using the binary search method. Using the Levenberg-Marquadt method we turn an initial transformation matrix to an optimal transformation matrix, and using this matrix combine a basic image with a input image.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.1-8
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• 2005

Image morphing to generate 2D transitions between images may be difficult even to express simple 3D transformations. In addition, previous view morphing method requires control points for postwarping, and is much affected by self- occlusion. This paper presents a new morphing algorithm that can generate automatically in-between scenes from un-calibrated images. Our algorithm rectifies input images based on the fundamental matrix, which is followed by linear interpolation with bilinear disparity map. In final, we generate in-between views by inverse mapping of homography between the rectified images. The proposed method nay be applied to photographs and drawings, because neither knowledge of 3D shape nor camera calibration, which is complex process generally, is required. The generated in-between views can be used in various application areas such as simulation system of virtual environment and image communication.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.199-206
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• 2012

Attempt to use as a marker of natural objects directly in the real world, but there is a way to use the accelerometer of the smartphone, to convert the Frontal-View virtual, because it asks only the pitch of the camera, from the side there is a drawback that can not be converted to images. The proposed algorithm, to obtain the rotation matrix of axis 3 pitch, roll, yaw, we set the reference point of the yaw of the target image. Then, to compensate for the rotation matrix to determine Myon'inji any floor, wall, the ceiling of the target image. Finally, to obtain the homography matrix for obtaining the Frontal-View to account for the difference between the gyro sensor coordinate system and image coordinate system, so we can get the Frontal-View from the captured images through the projection transformation was designed. Was tested to convert Frontal-View the picture was taken in an environment smartphone environment surrounding floor, walls and ceiling in order to evaluate the conversion program Frontal-View has been implemented, in this paper, design and The conversion algorithm implementation, it was confirmed that to convert a regular basis Frontal-View footage taken from multiple angles.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.762-766
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• 2003

In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

• 한국게임학회지
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• v.6 no.1
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• pp.48-51
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• 2009

디지털콘텐츠 산업분류체계를 비롯한 기존 방식으로는 현재의 디지털콘텐츠를 통찰력 있게 보기 힘듭니다. 이는 디지털콘텐츠 일반에 대한 인식의 틀이 부실한 탓입니다. 넓은 의미의 텍스트에서, 시점(視點)은 인식의 틀입니다. 문학과 미술, 영화와 관련된 콘텐츠 하부영역에서는 시점 연구가 체계적으로 이루어져 왔습니다. 이러한 시점 연구결과들을 통합하고 정리하여 디지털콘텐츠에 접목시켰습니다. 연구자는 콘텐츠와 그것의 사용자에 대한 관계를 두가지 기준으로 구분하였습니다. 하나는 콘텐츠와 사용자 자아인 페르소나 사이에 성립되는 '맥락인지적시점(ContextualView)'이고 나머지 하나는 콘텐츠를 비추는 눈인 '시각적시점(CameraView)'입니다. 맥락인지적시점은다시 '인물', '상대', '관객'으로 구분하였고 시각적시점은 '일인칭', '이인칭', '삼인칭'으로구분하였습니다. 그리고 이를 씨실과 날실로 연결하여 'CCmatrix'라 하였습니다. 그리고 월드 오브워크래프트를 'CCmatrix'로 분석하고 캐릭터 수준별로 일정한 패턴을 발견하였습니다. 또 다른 활용으로는 디지털콘텐츠의 시점역사를 정리하고 활용가능성을 보였습니다.