• Title/Summary/Keyword: 분할 영역법

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Volume Visualization System Using an Analytical Ray Casting (분석적 광선 추적법을 이용한 체적시각화 시스템)

  • Park, Hyun-Woo;Paik, Doo-Won;Jung, Moon-Ryul
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.2
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    • pp.477-487
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    • 2000
  • When volume data is visualized by the ray casting method, the color value of each pixel in the image is obtained by composing the color contributions of the sample points that lie on the ray cast from the pixel point. In most ray tracing methods including Levoy's classical method, the color composition is formulated as a summation of the color contributions of the discrete sample points. However, the more precise color composition is formulated as differential equations over the color contributions of the continuous sample points. The discrete formulation is used, because analytical solutions to the continuous formulations are hard to find. In this paper, however, we have discovered a semi-analytical solution to the continuous formulation of a typical ray tracing of volume data. We have applied both Levoy's method and ours to the same set of data, and compared the visual quality of both results. The comparison shows that our method produces a more fine-grained visualization of volume data.

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DOA Detection on Spilt-beam Transducers Using Quadrature sampling Method (스프리트-빔 변환기에서의 4분 샘플링을 이용한 도래방향 탐지)

  • Park Soon-Jong;Lee Mi-Hyun;Kim Moo-Joon;Kim Chun-Duck;Cha Kyung-Hwan
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.149-152
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    • 2004
  • 본 연구에서는 Split-beam 변환기에 적용 가능한 방향 탐지 알고리듬으로써 4분 샘플링에 의한 시간 영역에서의 음원 도래 방향 탐지법을 검토하고자 한다. 외부 잡음을 고려한 환경하에서도 완전 샘플링 및 4분 샘플링 후 주파수 영역에서의 시간 지연 계산법보다 4분 샘플링에 의한 시간 영역에서의 상호상관 기법이 경제적인 측면과 분해능의 측면에서 적절하다는 것을 확인하였다.

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Fuzzy-based Segmentation Algorithm for Brain Images (퍼지기반의 두뇌영상 영역분할 알고리듬)

  • Lee, Hyo-Jong
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.46 no.12
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    • pp.102-107
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    • 2009
  • As technology gets developed, medical equipments are also modernized and leading-edge systems, such as PACS become popular. Many scientists noticed importance of medical image processing technology. Technique of region segmentation is the first step of digital medical image processing. Segmentation technique helps doctors to find out abnormal symptoms early, such as tumors, edema, and necrotic tissue, and helps to diagnoses correctly. Segmentation of white matter, gray matter and CSF of a brain image is very crucial part. However, the segmentation is not easy due to ambiguous boundaries and inhomogeneous physical characteristics. The rate of incorrect segmentation is high because of these difficulties. Fuzzy-based segmentation algorithms are robust to even ambiguous boundaries. In this paper a modified Fuzzy-based segmentation algorithm is proposed to handle the noise of MR scanners. A proposed algorithm requires minimal computations of mean and variance of neighbor pixels to adjust a new neighbor list. With the addition of minimal compuation, the modified FCM(mFCM) lowers the rate of incorrect clustering below 30% approximately compared the traditional FCM.

Face Tracking and Recognition Algorithm Based On Object Segmentation and PCA (객체 분할 및 주성분 분석 기반의 얼굴 추적 인식 알고리즘)

  • 성민영;김대현;이응주
    • Proceedings of the Korea Multimedia Society Conference
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    • 2003.05b
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    • pp.435-440
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    • 2003
  • 본 논문에서는 실시간 출입통제시스템에 적용이 가긍한 복잡한 배경에서의 다중 얼굴 영역 검출과 추적을 통한 얼굴 인식 알고리즘을 제안하였다. 제안된 알고리즘에서는 배경영상과 입력된 연속적인 프레임간의 차영상을 적용함으로써 물체의 움직임을 감지한 후. IISI컬러 좌표모델을 이용하여 얼굴의 1차 후보 영역을 검출하고, 잡음제거를 위해 모폴로지 연산을 수행하였다 또한 Line Projection을 이용한 객체 분할법(Object Segmentation)으로 객체를 분할함으로써 다중 얼굴 영역을 추출하였다. 또한 추출된 얼굴영역에서 눈 영역 검출을 통해 각각의 얼굴 영역들을 검증하였으며 검증된 얼굴들의 최외각 4개의 좌표를 이용하여 얼굴 추적율을 높였다. 마지막으로 얼굴 인식은 추출된 얼굴 영역으로부터 주성분 분석(PCA : Principle Component Analysis)방법을 이용함으로써 97~98%의 높은 인식율을 보였다.

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Three-dimensional analysis of the mufflers by BEM (경계요소법에 의한 소음기의 3차원 해석)

  • 윤제원;임정빈;권영필
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1995.10a
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    • pp.19-24
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    • 1995
  • 단순한 형상의 소음기는 평면파이론에 의해 비교적 간단하게 음향성능을 해석적으로 구할 수 있다. 그러나 소음기의 형상이 복잡해지거나 해석하고자 하는 주파수의 범위가 평면파의 차단주파수 이상이 될 경우 소음기 내부의 음장이 평면파에서 벗어나게 되어 평면파 이론에 의한 해석은 실제와 상당한 오차가 발생하게 되므로 음장에 대한 3차원 해석이 필요하다. 이론적으로 3차원 문제를 해석할 수 있는 경우는 형상이 극히 단순한 경우에 국한되므로 유한요소법(FEM), 경계요소법(BEM)과 같은 수치해석적인 방법이 이용되고 있다. 경계요소법은 적분 커넬(kernel)의 특이성(singularity) 문제가 있지만 대상 영역의 경계면만을 이산화함으로써 모델링에 소요되는 시간과 노력을 절약할 수 있으므로 음향문제 해석에 있어서 효율적인 방법이라고 할 수 있다. 본 연구의 목적은 3차원 경계요소법 프로그램을 개발하고 평면파이론에 의한 해석이 어려운 여러가지 형태의 소음기에 대한 음향성능을 예측하고 실험으로 검증하는것이다. 특히, 단일영역으로 해석이 불가능한 다공형 소음기에 영역분할법을 적용하여 계산하고 결과를 검토하였다.

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Implementation of JBIG2 CODEC with Effective Document Segmentation (문서의 효율적 영역 분할과 JBIG2 CODEC의 구현)

  • 백옥규;김현민;고형화
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.6A
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    • pp.575-583
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    • 2002
  • JBIG2 is an International Standard fur compression of Bi-level images and documents. JBIG2 supports three encoding modes for high compression according to region features of documents. One of which is generic region coding for bitmap coding. The basic bitmap coder is either MMR or arithmetic coding. Pattern matching coding method is used for text region, and halftone pattern coding is used for halftone region. In this paper, a document is segmented into line-art, halftone and text region for JBIG2 encoding and JBIG2 CODEC is implemented. For efficient region segmentation of documents, region segmentation method using wavelet coefficient is applied with existing boundary extraction technique. In case of facsimile test image(IEEE-167a), there is improvement in compression ratio of about 2% and enhancement of subjective quality. Also, we propose arbitrary shape halftone region coding, which improves subjective quality in talc neighboring text of halftone region.

Region-based Canopy Cover Mapping Using Airborne Lidar Data (항공 라이다 자료를 이용한 영역 기반 차폐율 지도 제작)

  • Kim, Yong-Min;Eo, Yang-Dam;Jeon, Min-Cheol;Kim, Hyung-Tae;Kim, Chang-Jae
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.1
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    • pp.29-36
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    • 2011
  • The main purpose of this paper is to make a map showing canopy cover by using airborne Lidar data based on region. Watershed algorithm was applied to elevation data to conduct segmentation, and then canopy cover was estimated through the regions extracted. In the process of transforming point data to raster, we solved the problems about overestimation and underestimation by using frequency method. Also, canopy cover map could be produced with various scales by differing level of segmentation and it provides more accurate and precise information than ones of ordinary public forest map.

Zoning Method to Predict Contaminant Sources in Turbulent-Type Cleanroom (난류형 클린룸에서 영역분할법을 이용한 오염원 추정에 관한 연구)

  • Kim, D.K.;Sung, H.G.;Han, S.M.;Hwang, Y.K.
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.39 no.3
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    • pp.253-260
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    • 2015
  • Particle contamination in a cleanroom is very complex with a complicated process and several pieces of spreading equipment. Detailed information on the locations of the contamination sources and the path of the contamination is needed for economical and efficient control of the contaminant particles in such a cleanroom. An allocation method was developed to quantitatively predict the contamination generated from the pollution sources. In this paper, we propose a zoning method to accelerate the computation time for estimating the contributions. Our results showed that we can quantitatively estimate the amount of contamination generated from pollution sources.

Background Segmentation in Color Image Using Self-Organizing Feature Selection (자기 조직화 기법을 활용한 컬러 영상 배경 영역 추출)

  • Shin, Hyun-Kyung
    • The KIPS Transactions:PartB
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    • v.15B no.5
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    • pp.407-412
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    • 2008
  • Color segmentation is one of the most challenging problems in image processing especially in case of handling the images with cluttered background. Great amount of color segmentation methods have been developed and applied to real problems. In this paper, we suggest a new methodology. Our approach is focused on background extraction, as a complimentary operation to standard foreground object segmentation, using self-organizing feature selective property of unsupervised self-learning paradigm based on the competitive algorithm. The results of our studies show that background segmentation can be achievable in efficient manner.