• Title/Summary/Keyword: Object Boundary Point

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Spatial Analysis to Capture Person Environment Interactions through Spatio-Temporally Extended Topology (시공간적으로 확장된 토폴로지를 이용한 개인 환경간 상호작용 파악 공간 분석)

  • Lee, Byoung-Jae
    • Journal of the Korean Geographical Society
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    • v.47 no.3
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    • pp.426-439
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    • 2012
  • The goal of this study is to propose a new method to capture the qualitative person spatial behavior. Beyond tracking or indexing the change of the location of a person, the changes in the relationships between a person and its environment are considered as the main source for the formal model of this study. Specifically, this paper focuses on the movement behavior of a person near the boundary of a region. To capture the behavior of person near the boundary of regions, a new formal approach for integrating an object's scope of influence is described. Such an object, a spatio-temporally extended point (STEP), is considered here by addressing its scope of influence as potential events or interactions area in conjunction with its location. The formalism presented is based on a topological data model and introduces a 12-intersection model to represent the topological relations between a region and the STEP in 2-dimensional space. From the perspective of STEP concept, a prototype analysis results are provided by using GPS tracking data in real world.

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Data Structure Extraction of Boundary Segments by Region Labeling (영역 라벨링에 의한 경계선 세그먼트의 데이터 구조 추출)

  • 최환언;정광웅;김두영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.1
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    • pp.80-89
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    • 1992
  • This paper presents algorithms which are region labeling and data structure of a boundary segmentation as image intermediate description process. In the method, the algorithms are region labeling, boundary segmentation, line and curve fitting and extracting data structure of each segment. As a result, a data structure of image is described by a set of region number, segment number, line or curve, starting point and end point of each segment and coefficient of line or curve. These data structures would serve for higher level processing as object recognition. For example we will use this data structure to solve the correspondence problem of stereoscopic image information. And we verified these algorithms through the image reconstruction of data structure.

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Development of the Position Control Algorithm for Nonlinear Overhead Crane Systems (비선형 천장 크레인시스템의 위치제어 알고리즘 개발)

  • 이종규;이상룡
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.4
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    • pp.142-147
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    • 2000
  • An overhead crane system which transports an object by girder motion, trolley motion, and hoist motion becomes a nonlinear system because the length of a rope changes. To develope the position control algorithm for the nonlinear crane systems, we apply a nonlinear optimal control method which uses forward and backward difference methods and obtain optimal inputs. This method is suitable for the overhead crane system which is characterized by the differential equation of higher degree and swing motion. From the results of computer simulation, it is founded that the position of the overhead crane system is controlled, and the swing of the object is suppressed.

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A Study on Digital Image Processing Algorithm for Area Measurement of an Object Image by the Hierarchical Angle-Distance Graphs (계층적 각-거리 그래프를 이용한 물체 면적 측정을 위한 디지털 영상처리 알고리즘에 관한 연구)

  • Kim Woong-Ki;Ra Sung-Woong;Lee Jung-Won
    • The KIPS Transactions:PartB
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    • v.13B no.2 s.105
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    • pp.83-88
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    • 2006
  • Digital image processing algorithm was proposed to measure the area inside of an object image using angle-distance graph used to analyze the pattern of an object in the digital image processing techniques. The first angle-distance graph is generated from a point inside of an object area. The second angle-distance graphs are generated for the areas missed in the first graph by extracting the positions with large gradient in the first angle-distance graph. The order of the graph increases according to the complexity of an object pattern. Size of the area inside of an object boundary is measured by integrating square of distance multiplied by angle for each area from the hierarchical angie-distance graphs.

Extracting Building Boundary from Aerial LiDAR Points Data Using Extended χ Algorithm (항공 라이다 데이터로부터 확장 카이 알고리즘을 이용한 건물경계선 추출)

  • Cho, Hong-Beom;Lee, Kwang-Il;Choi, Hyun-Seok;Cho, Woo-Sug;Cho, Young-Won
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.2
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    • pp.111-119
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    • 2013
  • It is essential and fundamental to extract boundary information of target object via massive three-dimensional point data acquired from laser scanner. Especially extracting boundary information of manmade features such as buildings is quite important because building is one of the major components consisting complex contemporary urban area, and has artificially defined shape. In this research, extended ${\chi}$-algorithm using geometry information of point data was proposed to extract boundary information of building from three-dimensional point data consisting building. The proposed algorithm begins with composing Delaunay triangulation process for given points and removes edges satisfying specific conditions process. Additionally, to make whole boundary extraction process efficient, we used Sweep-hull algorithm for constructing Delaunay triangulation. To verify the performance of the proposed extended ${\chi}$-algorithm, we compared the proposed algorithm with Encasing Polygon Generating Algorithm and ${\alpha}$-Shape Algorithm, which had been researched in the area of feature extraction. Further, the extracted boundary information from the proposed algorithm was analysed against manually digitized building boundary in order to test accuracy of the result of extracting boundary. The experimental results showed that extended ${\chi}$-algorithm proposed in this research proved to improve the speed of extracting boundary information compared to the existing algorithm with a higher accuracy for detecting boundary information.

Motion Detection using Adaptive Background Image and A Net Model Pixel Space of Boundary Detection (적응적 배경영상과 그물형 픽셀 간격의 윤곽점 검출을 이용한 객체의 움직임 검출)

  • Lee Chang soo;Jun Moon seog
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.3C
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    • pp.92-101
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    • 2005
  • It is difficult to detect the accurate detection which leads the camera it moves follows in change of the noise or illumination and Also, it could be recognized with backgound if the object doesn't move during hours. In this paper, the proposed method is updating changed background image as much as N*M pixel mask as time goes on after get a difference between imput image and first background image. And checking image pixel can efficiently detect moving by computing fixed distance pixel instead of operate all pixel. Also, set up minimum area of object to use boundary point of object abstracted through checking image pixel and motion detect of object. Therefore motion detection is available as is fast and correct without doing checking image pixel every Dame. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.

KNOWLEDGE-BASED BOUNDARY EXTRACTION OF MULTI-CLASSES OBJECTS

  • Park, Hae-Chul;Shin, Ho-Chul;Lee, Jin-Sung;Cho, Ju-Hyun;Kim, Seong-Dae
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1968-1971
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    • 2003
  • We propose a knowledge-based algorithm for extracting an object boundary from low-quality image like the forward looking infrared image. With the multi-classes training data set, the global shape is modeled by multispace KL(MKL)[1] and curvature model. And the objective function for fitting the deformable boundary template represented by the shape model to true boundary in an input image is formulated by Bales rule. Simulation results show that our method has more accurateness in case of multi-classes training set and performs better in the sense of computation cost than point distribution model(PDM)[2]. It works well in distortion under the noise, pose variation and some kinds of occlusions.

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Lip Shape Representation and Lip Boundary Detection Using Mixture Model of Shape (형태계수의 Mixture Model을 이용한 입술 형태 표현과 입술 경계선 추출)

  • Jang Kyung Shik;Lee Imgeun
    • Journal of Korea Multimedia Society
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    • v.7 no.11
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    • pp.1531-1539
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    • 2004
  • In this paper, we propose an efficient method for locating human lips. Based on Point Distribution Model and Principle Component Analysis, a lip shape model is built. Lip boundary model is represented based on the concatenated gray level distribution model. We calculate the distribution of shape parameters using Gaussian mixture. The problem to locate lip is simplified as the minimization problem of matching object function. The Down Hill Simplex Algorithm is used for the minimization with Gaussian Mixture for setting initial condition and refining estimate of lip shape parameter, which can refrain iteration from converging to local minima. The experiments have been performed for many images, and show very encouraging result.

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A Proposal of Descent Multi-point Search Method and Its Learning Algorithm for Optimum Value (최적치 계산을 위한 점감다점탐색법과 그 학습 알고리즘의 제안)

  • 김주홍;공휘식;이광직
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.8
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    • pp.846-855
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    • 1992
  • In this paper, the decrease multipoint search method and Its learning algorithm for optimum value computatlon method of object function Is proposed. Using this method, the number of evaluation point according to searching time can t)e reduced multipoint of the direct search method by applying the unlivarlate method. And the learning algorithm can reprat the same search method in a new established boundary by using the searched result. In order to Investigate the efficience of algorithm, this method this method is applied to Rosenbrock and Powell, Colvelle function that are Impossible or uncertain in traditional direct search method. And the result of application, the optimum value searching oil every function Is successful. Especially, the algorithm is certified as a good calculation method for producing global(absolute) optimum value.

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DEVELOPMENT OF AN ORTHOGONAL DOUBLE-IMAGE PROCESSING ALGORITHM TO MEASURE BUBBLE VOLUME IN A TWO-PHASE FLOW

  • Kim, Seong-Jin;Park, Goon-Cherl
    • Nuclear Engineering and Technology
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    • v.39 no.4
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    • pp.313-326
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    • 2007
  • In this paper, an algorithm to reconstruct two orthogonal images into a three-dimensional image is developed in order to measure the bubble size and volume in a two-phase boiling flow. The central-active contour model originally proposed by P. $Szczypi\'{n}ski$ and P. Strumillo is modified to reduce the dependence on the initial reference point and to increase the contour stability. The modified model is then applied to the algorithm to extract the object boundary. This improved central contour model could be applied to obscure objects using a variable threshold value. The extracted boundaries from each image are merged into a three-dimensional image through the developed algorithm. It is shown that the object reconstructed using the developed algorithm is very similar or identical to the real object. Various values such as volume and surface area are calculated for the reconstructed images and the developed algorithm is qualitatively verified using real images from rubber clay experiments and quantitatively verified by simulation using imaginary images. Finally, the developed algorithm is applied to measure the size and volume of vapor bubbles condensing in a subcooled boiling flow.