• Title/Summary/Keyword: 3차원영상분석법

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동작 인식 방법에서 주성분 분석법의 활용에 관한 연구

  • Gwon, Yong-Man;Hong, Yeon-Ung
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.10a
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    • pp.105-109
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    • 2004
  • 동작(motion) 인식 방법 있어서 2차원 정보는 영상이라는 2차원 정보만을 이용하기 때문에 여러 가지 행동의 제약이 있으며 이것은 인식률을 저하시킬 뿐 아니라, 그 응용 면에서 자연스럽지 못하게 된다. 이러한 문제점을 보완하기 위하여 3차원 정보를 사용하는 시스템으로 발전하게 되었지만 영상 기반의 3차원 정보는 에러가 많이 포함되어 있을 뿐만 아니라 차원수가 높기 때문에 일정한 특징을 찾아내기 어렵다. 본 연구에서는 동작을 모델링하고 분석하기 위해 주성분 분석법을 사용하는 방법을 기술한다. 주성분 분석법은 낮은 차원의 영상 공간을 얻기 위해서 사용되는데, 이 방법을 사용함으로써 3차원 데이터가 가지는 에러의 영향을 줄일 수 있게 되고, 차원 축약의 효과를 얻을 수 있다.

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Simulation and Measurement of Signal Intensity for Various Tissues near Bone Interface in 2D and 3D Neurological MR Images (2차원과 3차원 신경계 자기공명영상에서 뼈 주위에 있는 여러 조직의 신호세기 계산 및 측정)

  • Yoo, Done-Sik
    • Progress in Medical Physics
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    • v.10 no.1
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    • pp.33-40
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    • 1999
  • Purpose: To simulate and measure the signal intensity of various tissues near bone interface in 2D and 3D neurological MR images. Materials and Methods: In neurological proton density (PD) weighted images, every component in the head including cerebrospinal fluid (CSF), muscle and scalp, with the exception of bone, are visualised. It is possible to acquire images in 2D or 3D. A 2D fast spin-echo (FSE) sequence is chosen for the 2D acquisition and a 3D gradient-echo (GE) sequence is chosen for the 3D acquisition. To find out the signal intensities of CSF, muscle and fat (or scalp) for the 2D spin-echo(SE) and 3D gradient-echo (GE) imaging sequences, the theoretical signal intensities for 2D SE and 3D GE were calculated. For the 2D fast spin-echo (FSE) sequence, to produce the PD weighted image, long TR (4000 ms) and short TE$_{eff}$ (22 ms) were employed. For the 3D GE sequence, low flip angle (8$^{\circ}$) with short TR (35 ms) and short TE (3 ms) was used to produce the PD weighted contrast. Results: The 2D FSE sequence has CSF, muscle and scalp with superior image contrast and SNR of 39 - 57 while the 3D GE sequence has CSF, muscle and scalp with broadly similar image contrast and SNR of 26 - 33. SNR in the FSE image were better than those in the GE image and the skull edges appeared very clearly in the FSE image due to the edge enhancement effect in the FSE sequence. Furthermore, the contrast between CSF, muscle and scalp in the 2D FSE image was significantly better than in the 3D GE image, due to the strong signal intensities (or SNR) from CSF, muscle and scalp and enhanced edges of CSF. Conclusion: The signal intensity of various tissues near bone interface in neurological MR images has been simulated and measured. Both the simulation and imaging of the 2D SE and 3D GE sequences have CSF, fat and muscle with broadly similar image intensity and SNR's and have succeeded in getting all tissues about the same signal. However, in the 2D FSE sequence, image contrast between CSF, muscle and scalp was good and SNR was relatively high, imaging time was relatively short.

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Principal Component Transformation of the Satellite Image Data and Principal-Components-Based Image Classification (위성 영상데이터의 주성분변환 및 주성분 기반 영상분류)

  • Seo, Yong-Su
    • Journal of the Korean Association of Geographic Information Studies
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    • v.7 no.4
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    • pp.24-33
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    • 2004
  • Advances in remote sensing technologies are resulting in the rapid increase of the number of spectral channels, and thus, growing data volumes. This creates a need for developing faster techniques for processing such data. One application in which such fast processing is needed is the dimension reduction of the multispectral data. Principal component transformation is perhaps the mostpopular dimension reduction technique for multispectral data. In this paper, we discussed the processing procedures of principal component transformation. And we presented and discussed the results of the principal component transformation of the multispectral data. Moreover principal components image data are classified by the Maximum Likelihood method and Multilayer Perceptron method. In addition, the performances of two classification methods and data reduction effects are evaluated and analyzed based on the experimental results.

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Phased Segmentation of Human Organs On the MDCT Scans (흉부 MDCT 영상을 이용한 신체 장기의 단계별 분할)

  • Shin, Min-Jun;Kim, Do-Yeon
    • Journal of Korea Multimedia Society
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    • v.14 no.11
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    • pp.1383-1391
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    • 2011
  • Following the appearance of the latest medical equipment with improved function, the importance of image analysis which enables effective image processing and analysis consistent with the hardware performance is on the rise. As well as, ongoing study is being done on the 2D medical image processing and 3D reconstruction. This paper segments chest CT images into each stage and finally shows 3D reconstruction of each segmented result. Among various image segmentation methods, Region Growing and apply sharpening and Gamma Controller as for image improvement for effective segmentation, image segmentation in order of bronchus and lung, bronchus, lung. Human organs image of segmented is use VTK(Visualization Toolkit) to make 3D reconstruction, two and three-dimensional medical image processing and analysis for lesions diagnosis are able to utilized.

3D Quantitative Analysis of Cell Nuclei Based on Digital Image Cytometry (디지털 영상 세포 측정법에 기반한 세포핵의 3차원 정량적 분석)

  • Kim, Tae-Yun;Choi, Hyun-Ju;Choi, Heung-Kook
    • Journal of Korea Multimedia Society
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    • v.10 no.7
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    • pp.846-855
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    • 2007
  • Significant feature extraction in cancer cell image analysis is an important process for grading cell carcinoma. In this study, we propose a method for 3D quantitative analysis of cell nuclei based upon digital image cytometry. First, we acquired volumetric renal cell carcinoma data for each grade using confocal laser scanning microscopy and segmented cell nuclei employing color features based upon a supervised teaming scheme. For 3D visualization, we used a contour-based method for surface rendering and a 3D texture mapping method for volume rendering. We then defined and extracted the 3D morphological features of cell nuclei. To evaluate what quantitative features of 3D analysis could contribute to diagnostic information, we analyzed the statistical significance of the extracted 3D features in each grade using an analysis of variance (ANOVA). Finally, we compared the 2D with the 3D features of cell nuclei and analyzed the correlations between them. We found statistically significant correlations between nuclear grade and 3D morphological features. The proposed method has potential for use as fundamental research in developing a new nuclear grading system for accurate diagnosis and prediction of prognosis.

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Frequency filtering effect on Fourier Transform 3-D Profilometry (푸리에 변환법을 이용한 3차원 위상측정에서의 필터 효과)

  • 박준식;나성웅;박승규;백성훈;이용주
    • Proceedings of the Optical Society of Korea Conference
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    • 2003.07a
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    • pp.296-297
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    • 2003
  • 본 연구에서는 푸리에 변환법에 의한 위상정보 추출 기술을 개발하고, 주파수 영역에서의 창함수 필터에 따른 위상추출 특성을 분석하였다. 푸리에 변환법은 위상이동법과는 달리 정현파 패턴이 투영된 하나의 영상만을 이용하여 3차원 형상정보를 추출할 수 있는 장점이 있다. 획득된 영상은 오일러 공식으로부터 다음과 같이 표현할 수 있다. (중략)

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Three-dimensional Distortion-tolerant Object Recognition using Computational Integral Imaging and Statistical Pattern Analysis (집적 영상의 복원과 통계적 패턴분석을 이용한 왜곡에 강인한 3차원 물체 인식)

  • Yeom, Seok-Won;Lee, Dong-Su;Son, Jung-Young;Kim, Shin-Hwan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.10B
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    • pp.1111-1116
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    • 2009
  • In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.

A Survey and Comparison of 3D Registration of Brain Images Between Marker Based and Feature Based Method (마커 기반과 특징기반에 기초한 뇌 영상의 3차원 정합방법의 비교 . 고찰)

  • 조동욱;김태우;신승수;김지영;김동원;조태경
    • The Journal of the Korea Contents Association
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    • v.3 no.3
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    • pp.85-97
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    • 2003
  • Medical tomography images like CT, MRI, PET, SPECT, fMRI, ett have been widely used for diagnosis and treatment of a patient and for clinical study in hospital. In many cases, tomography images are scanned in several different modalities or with time intervals for a single subject for extracting complementary information and comparing one another. 3D image registration is mapping two sets of images for comparison onto common 3D coordinate space, and may be categorized to marker -based matching and feature-based matching. 3D registration of brain images has an important role for visual and quantitative analysis in localization of treatment area of a brain, brain functional research, brain mapping research, and so on. In this article, marker-based and feature-based matching methods which are often used are introduced.

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Comparison and Analysis of Tomography Methods for Reconstruction of Three-dimensional Density Distributions in Two-phase Flows (2상유동장 내 3차원 밀도 분포 재건을 위한 토모그래피 기법의 성능 비교 분석)

  • Ko, Han-Seo;Kim, Yong-Jae
    • Journal of the Korean Society for Nondestructive Testing
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    • v.22 no.5
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    • pp.545-556
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    • 2002
  • Bubble behaviors in two-phase flows have been analyzed by tomography methods such as an algebraic reconstruction technique (ART) and a multiplicative algebraic reconstruction technique (MART). Initially, a bubbly flow and an annular flow have been investigated by cross-sectional view using computer synthesized phantoms. Two tomography methods have been compared to obtain more accurate results of the two-phase flows. Then, reconstruction of three-dimensional density distributions of phantoms with two and three bubbles have been accomplished by the MART method which provided the better results for the two-dimensional reconstructions accurately to analyze the bubble behaviors in the two-phase flow.

영상과 비디오로부터의 3차원 휴먼 자세 및 형상 복원 기술

  • ;Jeon, Seong-Ho;Jang, Ju-Yong;Park, In-Gyu
    • Broadcasting and Media Magazine
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    • v.26 no.3
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    • pp.59-70
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    • 2021
  • 미래의 메타버스 환경에서 3차원 가상 휴먼 표현은 매우 중요한 기술이며 영상 또는 비디오로부터 3차원 가상 휴먼 모델링이 핵심 기술이다. 본 기고문은 이 분야에 대한 충분한 사전 지식의 제공을 목표로 한다. 휴먼 복원 문제를 다루는 연구가 늘어남에 따라, 본 기고문에서 우리는 단일 영상 혹은 비디오로부터의 3차원 휴먼 복원 연구들에 대해 조사하고 그 결과를 다음과 같이 체계적으로 제시한다. 첫째, 3차원 휴먼 복원에 대한 배경 개념을 정의한다. 둘째, 제안된 분류법, 기여도, 정량적 결과에 따라 기존의 방법들을 상세하게 분석한다. 셋째, 관련 데이터셋 및 정성적 결과를 요약하여 연구자들이 이를 쉽게 활용할 수 있도록 한다. 마지막으로, 우리는 각 연구들을 분석하여 해당 방법들의 장점과 약점을 제시한다.