• 제목/요약/키워드: contour Tracking

검색결과 177건 처리시간 0.031초

Contour Conrtol of Mechatronic Servo Systems Using Chaotic Neural Networks (카오스 신경망을 이용한 기계적 서보 시스템의 경로 제어)

  • Choi, Won-Yong;Kim, Sang-Hee;Choi, Han-Go;Chae, Chang-Hyun
    • Proceedings of the KIEE Conference
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    • 대한전기학회 1997년도 하계학술대회 논문집 B
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    • pp.400-402
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    • 1997
  • This paper investigates the direct and adaptive control of mechatronic servo systems using modified chaotic neural networks (CNNs). For the performance evaluation of the proposed neural networks, we simulate the trajectory control of the X-Y table with direct control strategies. The CNN based controller demonstrates accurate tracking of the planned path and also shows superior performance on convergence and final error comparing with recurrent neural network(RNN) controller.

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Fatty Liver Classification of Ultrasonography Images using SOM Method (SOM 기법을 이용한 초음파 영상에서의 지방간 분류)

  • Park, Ha-Sil;Han, Min-Su;Kim, Young-Hoon;Kim, Kwang-Baek
    • Proceedings of the Korean Society of Computer Information Conference
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    • 한국컴퓨터정보학회 2014년도 제50차 하계학술대회논문집 22권2호
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    • pp.419-422
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    • 2014
  • 본 논문에서는 환자와 검사자에게 초음파 영상의 객관화된 정보를 정확하게 제공하기 위해 간과 신장의 초음파 영상에 SOM 기법을 적용하여 지방간 농도 수치를 분류하는 방법을 제시한다. 제안된 방법은 간, 신장 영역을 촬영한 초음파 영상에서 촬영정보나 눈금자 등과 같이 필요 없는 부분을 잡음으로 간주하여 제거한 Region Of Interest(ROI) 영상을 추출하고, 추출된 ROI 영상에서 명암대비를 강조하기 위해 Fuzzy Stretching 기법을 적용한다. Stretching된 영상에 Enhanced Average Binary와 Labeling 기법으로 적용하여 얻은 Contour 정보를 분석하여 잡음을 제거한 후, 지방간의 측정 영역을 추출한다. 추출된 간과 신장의 측정 영역에 SOM 기법을 적용하여 명암도 값을 분류한 후, 간과 신장의 실질 영역의 대표 명암도를 각각 추출하여 비교 분석한다. 제안된 방법을 초음파 영상에 적용한 결과, 효율적이고 객관적으로 간의 지방도를 분류할 수 있는 가능성을 확인하였다.

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A Study on the Extraction of Character from a Calling Card by using Contour Tracking Algorithm (윤곽선 추적 알고리즘을 이용한 명함 영상에서의 문자 추출에 관한 연구)

  • Park, So-Youn;Yun, Su-Jung;Lee, Jung-Ho;Kim, Myung-Jea;Lim, Eun-Kyoung;Kim, Kwang-Baek
    • Proceedings of the Korea Information Processing Society Conference
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    • 한국정보처리학회 2001년도 추계학술발표논문집 (상)
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    • pp.723-726
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    • 2001
  • 본 논문은 흑백 영문 명함 영상에서 개별 문자 추출에 관한 연구이다. 20개의 원본 명함 영상을 3배로 축소하고, 가로 세로 스미어링 기법을 이용하여 문자간의 여백을 제거하여, 문자 영역의 추출을 용이하게 하였다. 그리고, 윤곽선 추적 기법을 이용하여 문자열과 개별 문자를 추출하였다. 실험결과에서는 윤곽선 추적 알고리즘을 이용한 명함의 개별 문자 추출이 효과적인 것을 보인다.

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A Study on Identifier Extraction from Shipping Container Image by Using Fuzzy Binarization and Contour Tracking Algorithm (퍼지 이진화와 윤곽선 추적 알고리즘을 이용한 운송 컨데이너 영상의 식별자 추출에 관한 연구)

  • 윤형근;김광백
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 한국지능정보시스템학회 2003년도 춘계학술대회
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    • pp.490-494
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    • 2003
  • 운송 컨테이너의 식별자를 추출하고 인식하는 것은 컨테이너 식별자들의 크기나 위치가 정형화되어 있지 않고 외부의 잡음으로 인하여 식별자의 형태가 훼손되어 있기 때문에 어렵다. 본 논문에서는 이러한 특성을 고려하여 컨테이너 영상에 대해 Canny 마스크를 이용하여 에지를 검출하고, Canny 마스크가 적용된 영상에서 수직·수평 히스토그램을 적용하여 컨테이너의 식별자 영역을 추출한다. 추출된 컨테이너의 식별자 영역을 삼각형 타입의 퍼지 이진화 방법을 적용하여 이진화하고 이진화된 컨테이너 식별자 영역을 윤곽선 추적 알고리즘으로 개별 식별자를 추출한다. 제안된 방법의 성능을 평가하기 위하여 실제 컨테이너 영상에 적용한 결과, 기존의 방법보다 컨테이너의 식별자 추출에서 우수한 성능이 있음을 확인하였다.

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Effects of Aperture Densitv Distribution on the Flow Through a Rock Fracture with Line-Source and Line-Collection

  • Park, Chung-Kyun;Hahn, Pil-So
    • Nuclear Engineering and Technology
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    • 제30권6호
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    • pp.485-495
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    • 1998
  • Migration characteristics of tracers in a rock fracture in a case of line-source and line-collection was studied. The fracture plane was discretized into a square mesh to which variable apertures were assigned. The spatially varying apertures of a fracture were generated using a geostatistical method, based on a given aperture probability density distribution and a specified spatial correlation length. The flow potential and pressure at each node were computed. Calculations showed that fluid flow occurs predominantly through a few preferred paths. Hence, the large range of apertures in the fracture gives rise to flow channeling. The solute transport was calculated using a particle tracking method. The migration plumes of tracer between injection line and withdrawal line are displayed in contour plots. The elution curves are shown to be controlled by the aperture density distribution and to be insensitive to statistical realization and spatial correlation length.

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Multiple Properties-Based Moving Object Detection Algorithm

  • Zhou, Changjian;Xing, Jinge;Liu, Haibo
    • Journal of Information Processing Systems
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    • 제17권1호
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    • pp.124-135
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    • 2021
  • Object detection is a fundamental yet challenging task in computer vision that plays an important role in object recognition, tracking, scene analysis and understanding. This paper aims to propose a multiproperty fusion algorithm for moving object detection. First, we build a scale-invariant feature transform (SIFT) vector field and analyze vectors in the SIFT vector field to divide vectors in the SIFT vector field into different classes. Second, the distance of each class is calculated by dispersion analysis. Next, the target and contour can be extracted, and then we segment the different images, reversal process and carry on morphological processing, the moving objects can be detected. The experimental results have good stability, accuracy and efficiency.

Ship Design Visualization System base on Augmented Reality (증강현실 기반의 선박설계 시각화 시스템)

  • Park, Mi-Jeong;Yoo, Seung-Hyeok;Kim, Eung-Kon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 한국정보통신학회 2012년도 춘계학술대회
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    • pp.249-251
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    • 2012
  • Augmented Reality (AR) enables the enhanced realism and interaction by providing the overlaid digital information on the user's view of the physical world. In this paper, we propose an AR-based ship design visualization system for presenting ship 3D model in smart phones or table PCs. The proposed system compute corner points and feature points by contour finding method and harris corner detector, and build a ship-design drawing database. By using SURF algorithm, key feature points are extracted from ship-design drawing image which is obtained by mobile camera. Then ship-design drawing image is recognized by matching the feature points stored in DB and extracted key feature points. 3D ship structures are visualized by overlaying the ship-design drawing image on the smart phone or table PC's screen. Compared to conventional 2D ship-design, proposed system helps to easily understand the structures of the ship and reduce the business design period. Thus, Enhanced competitiveness of business is expected.

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A Study on the Recognition of Car Plate using an Enhanced Fuzzy ART Algorithm (개선된 퍼지 ART 알고리즘을 이용한 차량 번호판 인식에 관한 연구)

  • 임은경;김광백
    • Journal of Korea Multimedia Society
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    • 제3권5호
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    • pp.433-444
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    • 2000
  • The recognition of car plate was investigated by means of the enhanced fuzzy ART algorithm. The morphological information of horizontal and vertical edges was used to extract a plate area from a car image. In addition, the contour tracking algorithm by utilizing the SOFM was applied to extract the specific area which includes characters from an extracted plate area. The extracted characteristic area was recognized by using the enhanced fuzzy ART algorithm. In this study we propose the novel fuzzy ART algorithm different from the conventional fuzzy ART algorithm by the dynamical establishment of the vigilance threshold which shows a tolerance limit of unbalance between voluntary and saved patterns for clustering. The extraction rate obtained by using the morphological information of horizontal and vertical edges showed better results than that from the color information of RGB and HSI. Furthermore, the recognition rate of the enhanced fuzzy ART algorithm was improved much more than that of the conventional fuzzy ART and SOFM algorithms.

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A Study on Recognition of Car License Plate using Dynamical Thresholding Method and Kohonen Algorithm (동적인 임계화 방법과 코호넨 알고리즘을 이용한 차량 번호판 인식에 관한 연구)

  • 김광백;노영욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제26권12A호
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    • pp.2019-2026
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    • 2001
  • In this paper, we proposed the car license plate extraction and recognition algorithm using both the dynamical thresholding method and the kohonen algorithm. In general, the areas of car license plate in the car images have distinguishing characteristics, such as the differences in intensity between the areas of characters and the background of the plates, the fixed ratio of width to height of the plates, and the higher dynamical thresholded density rate 7han the other areas, etc. Taking advantage of the characteristics, the thresholded images were created from the original images, and also the density rates were computed. A candidate area was selected, whose density rate was corresponding to the properties of the car license plate obtained from the car license plate. The contour tracking method by utilizing the Kohonen algorithm was applied to extract the specific area which included characters and numbers from an extracted plate area. The characters and numbers of the license place were recognized by using Kohonen algorithm. Kohonen algorithm was very effective o? suppressing noises scattered around the contour. In this study, 80 car images were tested. The result indicate that we proposed is superior in performance.

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Skin Color Based Hand and Finger Detection for Gesture Recognition in CCTV Surveillance (CCTV 관제에서 동작 인식을 위한 색상 기반 손과 손가락 탐지)

  • Kang, Sung-Kwan;Chung, Kyung-Yong;Rim, Kee-Wook;Lee, Jung-Hyun
    • The Journal of the Korea Contents Association
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    • 제11권10호
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    • pp.1-10
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    • 2011
  • In this paper, we proposed the skin color based hand and finger detection technology for the gesture recognition in CCTV surveillance. The aim of this paper is to present the methodology for hand detection and propose the finger detection method. The detected hand and finger can be used to implement the non-contact mouse. This technology can be used to control the home devices such as home-theater and television. Skin color is used to segment the hand region from background and contour is extracted from the segmented hand. Analysis of contour gives us the location of finger tip in the hand. After detecting the location of the fingertip, this system tracks the fingertip by using only R channel alone, and in recognition of hand motions to apply differential image, such as the removal of useless image shows a robust side. We explain about experiment which relates in fingertip tracking and finger gestures recognition, and experiment result shows the accuracy above 96%.