• Title/Summary/Keyword: 동적영역분할

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Automatic prostate segmentation method on dynamic MR images using non-rigid registration and subtraction method (동작 MR 영상에서 비강체 정합과 감산 기법을 이용한 자동 전립선 분할 기법)

  • Lee, Jeong-Jin;Lee, Ho;Kim, Jeong-Kon;Lee, Chang-Kyung;Shin, Yeong-Gil;Lee, Yoon-Chul;Lee, Min-Sun
    • Journal of Korea Multimedia Society
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    • v.14 no.3
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    • pp.348-355
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    • 2011
  • In this paper, we propose an automatic prostate segmentation method from dynamic magnetic resonance (MR) images. Our method detects contrast-enhanced images among the dynamic MR images using an average intensity analysis. Then, the candidate regions of prostate are detected by the B-spline non-rigid registration and subtraction between the pre-contrast and contrast-enhanced MR images. Finally, the prostate is segmented by performing a dilation operation outward, and sequential shape propagation inward. Our method was validated by ten data sets and the results were compared with the manually segmented results. The average volumetric overlap error was 6.8%, and average absolute volumetric measurement error was 2.5%. Our method could be used for the computer-aided prostate diagnosis, which requires an accurate prostate segmentation.

A Voice Boundary Detection Method Using Dynamic Parameters Based On Neural Network (신경망 기반의 동적 파라미터들을 이용한 음성 경계 추출)

  • 마창수;김계영;최형일
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.616-618
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    • 2002
  • 본 논문에서는 음성인식 성능을 높이기 위한 기본적 단계인 음성과 비음성 부분의 경계를 추출하는 음성 경계 추출 방법을 제안한다. 음성경계 추출을 위한 특징들로는 시간영역 분할 파라미터인 ZCR, MA를 사용하고 주파수 영역 분할 파라미터로 주파수 대역 파워 에너지 (Frequency band power energy), 포만트 계수 (Formant coefficient)를 사용하였고 각 파라미터들을 이용하여 음성 경계를 결정할 때 경험에 의해 임계치를 결정하는 단점을 보안하기 위해서 신경망을 이용한다. 신경망의 가중치와 임계치들은 지도 학습을 통해 최적화 되고, 학습을 통해 구성된 망을 음성과 비음성의 경계치 구분에 사용한다.

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An Illumination and Background-Robust Hand Image Segmentation Method Based on the Dynamic Threshold Values (조명과 배경에 강인한 동적 임계값 기반 손 영상 분할 기법)

  • Na, Min-Young;Kim, Hyun-Jung;Kim, Tae-Young
    • Journal of Korea Multimedia Society
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    • v.14 no.5
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    • pp.607-613
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    • 2011
  • In this paper, we propose a hand image segmentation method using the dynamic threshold values on input images with various lighting and background attributes. First, a moving hand silhouette is extracted using the camera input difference images, Next, based on the R,G,B histogram analysis of the extracted hand silhouette area, the threshold interval for each R, G, and B is calculated on run-time. Finally, the hand area is segmented using the thresholding and then a morphology operation, a connected component analysis and a flood-fill operation are performed for the noise removal. Experimental results on various input images showed that our hand segmentation method provides high level of accuracy and relatively fast stable results without the need of the fixed threshold values. Proposed methods can be used in the user interface of mixed reality applications.

Extraction and Recognition of the Car License Plate using Dynamic Candidate Scope and Double Template Matching (동적 후보영역과 이중 템플릿매칭을 이용한 차량 번호판 추출 및 인식)

  • Jeon, Jin-Seok;Paek, Nam-Soo;Lee, Byung-Sun;Rhee, Eun-Joo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11a
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    • pp.751-754
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    • 2002
  • 본 논문에서는 획득한 차량 영상에서, 차량 번호판의 후보영역을 동적으로 할당하여 번호판을 추출하고, 이중 템플릿 매칭을 이용하여 인식하는 방법을 제안하였다. 차량 번호판 영역은 다른 영역에 비해 영상의 밀도값이 높다는 것을 근거로, 후보영역을 투영하여 추출된 영상의 밀도값과 기준밀도값을 비교하여 차이가 임계값 이하를 만족한 때 차량 번호판 영역으로 추출하고 만족하지 않을 때는 다음 후보영역을 투영하여 차량 번호판 영역을 추출하였다. 추출된 번호판 영역에서 문자와 숫자영역으로 분할된 입럭패턴과 표준패턴을 흑화소로 1차 매칭하고, 이 중 유사도가 높은 표준패턴과 다시 백화소로 2차 매칭하는 이중 템플릿 매칭으로 인식하였다.

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A Hierarchical Image Mosaicing using Camera and Object Parameters for Efficient Video Database Construction (효율적인 비디오 데이터베이스 구축을 위해 카메라와 객체 파라미터를 이용한 계층형 영상 모자이크)

  • 신성윤;이양원
    • Journal of Korea Multimedia Society
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    • v.5 no.2
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    • pp.167-175
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    • 2002
  • Image Mosaicing creates a new image by composing video frames or still images that are related, and performed by arrangement, composition and redundancy analysis of images. This paper proposes a hierarchical image mosaicing system using camera and object parameters far efficient video database construction. A tree-based image mosiacing has implemented for high-speed computation time and for construction of static and dynamic image mosaic. Camera parameters are measured by using least sum of squared difference and affine model. Dynamic object detection algorithm has proposed for extracting dynamic objects. For object extraction, difference image, macro block, region splitting and 4-split detection methods are proposed and used. Also, a dynamic positioning method is used for presenting dynamic objects and a blurring method is used for creating flexible mosaic image.

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Sibling Node Clustering in Tree-based Spatial Indexes for Efficient Processing of Spatial Queries (효율적 공간 질의 처리를 위한 트리 구조 공간 색인의 형제 노드 클러스터링)

  • Kim, Gi-Hong;Cha, Sang-Gyun
    • Journal of KIISE:Software and Applications
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    • v.26 no.4
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    • pp.487-499
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    • 1999
  • 공간 또는 다차원 데이터베이스에서는 노드영역의 중첩 및 다차원성 때문에 다수의 색인 노드를 읽어야 하는 질의가 빈번히 나타난다. 이와 관련하여 기존 연구에서는 질의를 처리하기 위해 읽어야하는 노드의 수를 줄일수 있는 새로운 색인방법을 다수 제안하였으며 본 논문에서는 같은 수의 노드를 디스크에서 빨리 읽을 수 있도록 클러스터링하는 간단한 방법을 제안한다. 제안된 방법은 노드를 형제 노드 군으로 분할하여 한 형제 노드군을 연속된 디스크 블록 군에 저장하고 노드 분할 또는 병합이 일어날때도 이런 클러스터링을 동적으로 유지한다. 약 130,000개의 TIGER 데이터와 Hilbert R-트리를 이용할 실험 결과 , 제안된 형제 노드 클러스터링을 통해 공간 영역 질의, 공간 근접질의, 공간조인 질의 등을 처리할 때 필요한 디스크 접근 시간을 최대 86%까지 줄일 수 있었다. 반면 색인 갱신과정에서 형제노드 클러스터링을 동적으로 유지하는 데 필요한 디스크 읽기 쓰기 회수의 증가량은 1% 미만밖에 되지 않았다.

An Automatic Extraction Method of Glomerulus Region from Human Renal Tissue Image (신장조직영상에서 사구체 영역의 자동 추출법)

  • Kim, Eung-Kyeu;Lee, Choong-Ho
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2006.06a
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    • pp.21-24
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    • 2006
  • 본 논문에서는 신장조직 영상에서 사구체 영역을 자동적으로 추출하는 방법을 제안한다. 사구체 조직은 신장의 상태를 나타내는 많은 정보를 포함하고 있기 때문에 사구체 영역의 추출은 신장 검사를 자동화하기 위한 첫 번째 단계이다. 그러나 사구체 영역을 단순한 2치화 방법으로 직접 추출함은 어려운 일이다. 이에 본 연구자들은 우선, 가우스 함수에 의한 원영상의 빛바랜 영상을 동적인 임계값으로 사용함으로써 원영상을 2치화한다. 다음으로, 획득한 영상으로부터 간단한 영상처리 기법에 의한 사구체 영역의 경계 에지를 포함하는 모든 에지를 추출한다. 그 다음으로 사구체 영역의 경계 에지를 판별함으로써 사구체 영역을 추출하였다. 이 방법은 다수의 샘플에 적용해서 유효성을 확인한 바 양호한 결과를 얻을 수 있었다.

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Unsupervised Segmentation of Objects using Genetic Algorithms (유전자 알고리즘 기반의 비지도 객체 분할 방법)

  • 김은이;박세현
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.4
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    • pp.9-21
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    • 2004
  • The current paper proposes a genetic algorithm (GA)-based segmentation method that can automatically extract and track moving objects. The proposed method mainly consists of spatial and temporal segmentation; the spatial segmentation divides each frame into regions with accurate boundaries, and the temporal segmentation divides each frame into background and foreground areas. The spatial segmentation is performed using chromosomes that evolve distributed genetic algorithms (DGAs). However, unlike standard DGAs, the chromosomes are initiated from the segmentation result of the previous frame, then only unstable chromosomes corresponding to actual moving object parts are evolved by mating operators. For the temporal segmentation, adaptive thresholding is performed based on the intensity difference between two consecutive frames. The spatial and temporal segmentation results are then combined for object extraction, and tracking is performed using the natural correspondence established by the proposed spatial segmentation method. The main advantages of the proposed method are twofold: First, proposed video segmentation method does not require any a priori information second, the proposed GA-based segmentation method enhances the search efficiency and incorporates a tracking algorithm within its own architecture. These advantages were confirmed by experiments where the proposed method was success fully applied to well-known and natural video sequences.

Adaptive Segmentation Approach to Extraction of Road and Sky Regions (도로와 하늘 영역 추출을 위한 적응적 분할 방법)

  • Park, Kyoung-Hwan;Nam, Kwang-Woo;Rhee, Yang-Won;Lee, Chang-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.7
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    • pp.105-115
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    • 2011
  • In Vision-based Intelligent Transportation System(ITS) the segmentation of road region is a very basic functionality. Accordingly, in this paper, we propose a region segmentation method using adaptive pattern extraction technique to segment road regions and sky regions from original images. The proposed method consists of three steps; firstly we perform the initial segmentation using Mean Shift algorithm, the second step is the candidate region selection based on a static-pattern matching technique and the third is the region growing step based on a dynamic-pattern matching technique. The proposed method is able to get more reliable results than the classic region segmentation methods which are based on existing split and merge strategy. The reason for the better results is because we use adaptive patterns extracted from neighboring regions of the current segmented regions to measure the region homogeneity. To evaluate advantages of the proposed method, we compared our method with the classical pattern matching method using static-patterns. In the experiments, the proposed method was proved that the better performance of 8.12% was achieved when we used adaptive patterns instead of static-patterns. We expect that the proposed method can segment road and sky areas in the various road condition in stable, and take an important role in the vision-based ITS applications.

A Spatial Split Method for Processing of Region Monitoring Queries (영역 모니터링 질의 처리를 위한 공간 분할 기법)

  • Chung, Jaewoo;Jung, HaRim;Kim, Ung-Mo
    • Journal of Internet Computing and Services
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    • v.19 no.1
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    • pp.67-76
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    • 2018
  • This paper addresses the problem of efficient processing of region monitoring queries. The centralized methods used for existing region monitoring query processing assumes that the mobile object periodically sends location-updates to the server and the server continues to update the query results. However, a large amount of location updates seriously degrade the system performance. Recently, some distributed methods have been proposed for region monitoring query processing. In the distributed methods, the server allocates to all objects i) a resident domain that is a subspace of the workspace, and ii) a number of nearby query regions. All moving objects send location updates to the server only when they leave the resident domain or cross the boundary of the query region. In order to allocate the resident domain to the moving object along with the nearby query region, we use a query index structure that is constructed by splitting the workspace recursively into equal halves. However, However, the above index structure causes unnecessary division, resulting in deterioration of system performance. In this paper, we propose an adaptive split method to reduce unnecessary splitting. The workspace splitting is dynamically allocated i) considering the spatial relationship between the query region and the resultant subspace, and ii) the distribution of the query region. We proposed an enhanced QR-tree with a new splitting method. Through a set of simulations, we verify the efficiency of the proposed split methods.