• Title/Summary/Keyword: Range Segmentation

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Video image retrieval on the basis of subregional co-occurrence matrix texture features and normalised correlation (PIM 기반 국부적 Co-occurrence 행렬 및 normalised correlation를 이용한 효율적 비디오 검색 방법)

  • 김규헌;정세윤;전병태;이재연;배영래
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.601-604
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    • 1999
  • This Paper proposes the simple and efficient image retrieval algorithm using subregional texture features. In order to retrieve images in terms of its contents, it is required to obtain a precise segmentation. However, it is very difficult and takes a long computing time. Therefore. this paper proposes a simple segmentation method, which is to divide an image into high and low entropy regions by using Picture Information Measure (PIM). Also, in order to describe texture characteristics of each region, this paper suggest six different texture features produced on the basis of co-occurrence matrix. For an image retrieval system, a normalised correlation is adopted as a similarity function, which is not dependent on the range of each texture feature values. Finally, this proposed algorithm is applied to a various images and produces competitive results.

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Analysis and Design of Wideband Rotman Lens with Exponential Taper Using Contour Integral and Segmentation Method (경계적분법과 세그멘테이션 기법을 이용한 광대역 지수함수 테이퍼 로트만렌즈의 해석 및 설계)

  • 이광일;이일규;오승엽
    • Proceedings of the IEEK Conference
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    • 2003.07a
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    • pp.629-632
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    • 2003
  • This paper has been studied analysis and design of microstrip Rotman lens operating over wide band and wide steering angle by the contour integral method along with the segmentation method. All mutual coupling, internal reflections between ports with exponential taper are taken into account. Equally spaced ports are designed and realized which gives less amplitude ripple at array ports. The measured results of 12 input and 12 output lens show $\pm$1.8 dB insertion loss deviation over 6~18GHz wide frequency range and beam steering accuracy less than 1$^{\circ}$ over $\pm$53$^{\circ}$ angle and agrees well with the analysis results.

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Multi-channel Lidar Processing for Terrain Segmentation (지형분할을 위한 다채널 라이다 데이터 처리)

  • Chu, Phuong;Cho, Seoungjae;Sim, Sungdae;Kwak, Kiho;Cho, Kyungeun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2016.10a
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    • pp.681-682
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    • 2016
  • In this study we propose a novel approach to segment a terrain in two parts: ground and none-ground. The terrain is gained by a multi-channel 3D laser range sensor. We process each vertical line in each frame data. The vertical line is bounded by the sensor's position and a point in the largest circle of the frame. We consider each pair of two consecutive points in each line to find begin-ground and end-ground points. All points placed between a begin-ground point and an end-ground point are ground ones. The other points are none-ground. After examining all vertical lines in the frame, we obtain the terrain segmentation result.

Stereoscopic Millimeter-wave Image Processing for Depth Information

  • Park, Min-Chul;Son, Jung-Young
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.1022-1024
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    • 2009
  • Stereoscopic Images provide depth information with the relative distances between the objects in the images. There are many different ways to extract disparity maps from the visible spectral images. For the infrared spectral range, the same approach cannot be utilized for the innate low resolution and colorless features because typical methods require corresponding features between the images. The authors suggest a new approach that makes use of image segmentation to obtain depth information for stereoscopic millimeter-wave images. For image segmentation a selective visual attention model based on the theory of a feature-integration of attention is used. Experimental results show the proposed method provides reasonable depth information for object shape recognition and display.

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Object-Based Video Segmentation Using Spatio-temporal Entropic Thresholding and Camera Panning Compensation (시공간 엔트로피 임계법과 카메라 패닝 보상을 이용한 객체 기반 동영상 분할)

  • 백경환;곽노윤
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.4 no.3
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    • pp.126-133
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    • 2003
  • This paper is related to a morphological segmentation method for extracting the moving object in video sequence using global motion compensation and two-dimensional spatio-temporal entropic thresholding. First, global motion compensation is performed with camera panning vector estimated in the hierarchical pyramid structure constructed by wavelet transform. Secondly, the regions with high possibility to include the moving object between two consecutive frames are extracted block by block from the global motion compensated image using two-dimensional spatio-temporal entropic thresholding. Afterwards, the LUT classifying each block into one among changed block, uncertain block, stationary block according to the results classified by two-dimensional spatio-temporal entropic thresholding is made out. Next, by adaptively selecting the initial search layer and the search range referring to the LUT, the proposed HBMA can effectively carry out fast motion estimation and extract object-included region in the hierarchical pyramid structure. Finally, after we define the thresholded gradient image in the object-included region, and apply the morphological segmentation method to the object-included region pixel by pixel and extract the moving object included in video sequence. As shown in the results of computer simulation, the proposed method provides relatively good segmentation results for moving object and specially comes up with reasonable segmentation results in the edge areas with lower contrast.

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Range image reconstruction based on multiresolution surface parameter estimation (다해상도 면 파라미터 추정을 이용한 거리영상 복원)

  • 장인수;박래홍
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.6
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    • pp.58-66
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    • 1997
  • This paper proposes a multiresolution surface parameter estimation method for range images. Based on robust estimation of surface parameters, it approximates a patch to a planar surface in the locally adaptive window. Selection of resolution is made pixelwise by comparing a locally computed homogeneity measure with th eglobal threshold determined by te distribution of the approximation error. The proposed multiresolution surface parameter estimation method is applied to range image reconstruction. Computer simulation results with noisy rnag eimages contaminated by additive gaussian noise and impulse noise show that the proposed multiresolution reconstruction method well preserves step and roof edges compared with the conventional methods. Also the segmentation method based on the estimated surface parameters is shown to be robust to noise.

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Range image segmentation and classiication using cooperative relaxational algorithm between H-K curvatures (평균 곡률과 가우시안 곡률의 상호 셥동 이완 알고리즘을 이용한 거리 영상의 분할과 분류)

  • 정인갑;김용석;현기호;이응주;하영호
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.8
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    • pp.84-91
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    • 1997
  • The range image is divided into surface regions which are homogeneous in their intrinsic properties. In this paper, we use cooperative relaxational algorithm between curvatures to escape local minima and choose optimal possibility to reserve edge. Cooperative relaxational algorithm between curvatures is relaxation process in which weights of center pixel;s and neighbor pixel's possiblility are determined adaptively by using deviation of curvatures. Experimental resutls show that the proposed method segments and classifies the range images more accurately compared to the other relational algorithms.

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Green-Blue Stripe Pattern for Range Sensing from Single Image (녹-청 띠 패턴을 이용한 단일이미지로부터의 거리영상획득)

  • Changsoo Je;Park, Kyuhyoung;Lee, Sang-Wook
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.10b
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    • pp.661-663
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    • 2003
  • In this paper, we present new methods for rapid high-resolution range sensing using green-blue stripe pattern. We use green and blue for designing high-frequency stripe projection pattern. For accurate and reliable range recovery, we identify the stripe patterns by our color-stripe segmentation and unwrapping method. The experimental result for a naked human face shows the effectiveness of our method.

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Human Assisted Fitting and Matching Primitive Objects to Sparse Point Clouds for Rapid Workspace Modeling in Construction Automation (-건설현장에서의 시공 자동화를 위한 Laser Sensor기반의 Workspace Modeling 방법에 관한 연구-)

  • KWON SOON-WOOK
    • Korean Journal of Construction Engineering and Management
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    • v.5 no.5 s.21
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    • pp.151-162
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    • 2004
  • Current methods for construction site modeling employ large, expensive laser range scanners that produce dense range point clouds of a scene from different perspectives. Days of skilled interpretation and of automatic segmentation may be required to convert the clouds to a finished CAD model. The dynamic nature of the construction environment requires that a real-time local area modeling system be capable of handling a rapidly changing and uncertain work environment. However, in practice, large, simple, and reasonably accurate embodying volumes are adequate feedback to an operator who, for instance, is attempting to place materials in the midst of obstacles with an occluded view. For real-time obstacle avoidance and automated equipment control functions, such volumes also facilitate computational tractability. In this research, a human operator's ability to quickly evaluate and associate objects in a scene is exploited. The operator directs a laser range finder mounted on a pan and tilt unit to collect range points on objects throughout the workspace. These groups of points form sparse range point clouds. These sparse clouds are then used to create geometric primitives for visualization and modeling purposes. Experimental results indicate that these models can be created rapidly and with sufficient accuracy for automated obstacle avoidance and equipment control functions.

A study on range image segmentation and surface feature extraction (거리 영상 분할과 면 특징 추출에 관한 연구)

  • 현대환;김대현;이선호;최종수
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.509-511
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    • 1999
  • 본 논문에서는 일반적으로 영역 기반형 분할방법보다 우수한 분할결과와 계산의 효율성을 가지는 경계선 기반형 방법의 하나인 scan line approximation 방법을 응용함으로써 경계선의 기하학적 해석이 가능하도록 하는 경계선 강도(edge intensity) 정보를 제공한다. 따라서 면 특성과 국부적인 면 특성인 면 법선과 면 곡률정보 없이 잡음에 강건하고 계산의 효율성에서 우수한 거리영상분할 방법을 제안한다. 합성 거리영상을 대상으로 scan line approximation 방법을 응용하여 얻어진 경계선을 경계선 그룹화의 영역 레이블링을 거쳐서 면 특징을 추출하였다.

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