• Title/Summary/Keyword: 중심점 추출

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Lane Departure Warning Algorithm Through Single Lane Extraction and Center Point Analysis (단일차선추출 및 중심점 분석을 통한 차선이탈검출 알고리즘)

  • Bae, Jung-Ho;Kim, Soo-Woong;Lee, Hae-Yeoun;Lee, Hyun-Ah;Kim, Byeong-Man
    • The KIPS Transactions:PartB
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    • v.16B no.1
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    • pp.35-46
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    • 2009
  • Lane extraction and lane departure warning algorithms using the image sensor attached in the vehicle are addressed. With the research about intelligent automobile, there have been many algorithms about lane recognition and lane departure warning system. However, since these algorithms require to detect 2 lanes, the high time complexity and the low recognition rate under various driving circumstances are critical problems. In this paper, we present a lane departure warning algorithm using single lane extraction and center point analysis that achieves the fast processing time and high detection rate. From the geometry between camera and objects, the region of interest (ROI) is determined and splitted into two parts. Hough transform detects the part of the lane. After the detected lane is restored to have a pre-determined size, lane departure is estimated by calculating the distance from the center point. On real driving environments, the presented algorithm is compared with previous algorithms. Experiment results support that the presented algorithm is fast and accurate.

A Real-time Augmented Reality System using Hand Geometric Characteristics based on Computer Vision (손의 기하학적인 특성을 적용한 실시간 비전 기반 증강현실 시스템)

  • Choi, Hee-Sun;Jung, Da-Un;Choi, Jong-Soo
    • Journal of Korea Multimedia Society
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    • v.15 no.3
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    • pp.323-335
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    • 2012
  • In this paper, we propose an AR(augmented reality) system using user's bare hand based on computer vision. It is important for registering a virtual object on the real input image to detect and track correct feature points. The AR systems with markers are stable but they can not register the virtual object on an acquired image when the marker goes out of a range of the camera. There is a tendency to give users inconvenient environment which is limited to control a virtual object. On the other hand, our system detects fingertips as fiducial features using adaptive ellipse fitting method considering the geometric characteristics of hand. It registers the virtual object stably by getting movement of fingertips with determining the shortest distance from a palm center. We verified that the accuracy of fingertip detection over 82.0% and fingertip ordering and tracking have just 1.8% and 2.0% errors for each step. We proved that this system can replace the marker system by tacking a camera projection matrix effectively in the view of stable augmentation of virtual object.

Study on Defect Cell Extraction of TFT-LCD Panel (TFT-LCD 결함패턴 추출에 관한 연구)

  • Cho, Jae-Soo;Ha, Gwang-Sung;Lee, Jin-Wook;Kim, Dong-Hyun;Jeon, Edward
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.151-152
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    • 2007
  • 본 논문은 TFT-LCD 영상에서 결함을 자동검색하여 결함이 있는 LCD 영상의 경우 결함이 있는 LCD 패턴을 정확하게 추출해 내는 방법을 제안하였다. TFT-LCD 영상에서 결함이 있는 LCD 패턴 검색은 세단계로 이루어진다. 1단계는 먼저 입력영상에서 LCD 패턴영상의 특징을 이용하여 각 LCD 패턴의 기준점을 찾는다. 2단계는 1단계에서 찾은 여러 기준점 중에서 필터링과정을 통하여 정확한 한 개의 기준점을 최종 선택한다. 마지막으로 3단계에서는 최종적으로 선택된 기준점을 이용하여 결함정의(결함중심 및 결함사이즈)를 이용하여 결함이 포함되어 있는 LCD 패턴을 추출한다. 제안된 결함패턴 추출 알고리즘의 정확성은 컴퓨터 시뮬레이션을 통하여 그 효용성을 증명하였다.

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Valve Modeling and Model Extraction on 3D Point Cloud data (잡음이 있는 3차원 점군 데이터에서 밸브 모델링 및 모델 추출)

  • Oh, Ki Won;Choi, Kang Sun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.12
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    • pp.77-86
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    • 2015
  • It is difficult to extract small valve automatically in noisy 3D point cloud obtained from LIDAR because small object is affected by noise considerably. In this paper, we assume that the valve is a complex model consisting of torus, cylinder and plane represents handle, rib and center plane to extract a pose of the valve. And to extract the pose, we received additional input: center of the valve. We generated histogram of distance between the center and each points of point cloud, and obtain pose of valve by extracting parameters of handle, rib and center plane. Finally, the valve is reconstructed.

The shape representation of 3D object using a quadric polynomial (2차 다항식을 이용한 3차원 물체의 형상 표현)

  • 현대환;이선호;김태은;최종수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.9B
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    • pp.1251-1258
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    • 2001
  • 본 논문은 2차 다항식을 이용하여 3차원 물체의 표면 특징을 추출하고 표현하는 방법을 제안한다. 본 연구는 수정된 스캔 라인 기법을 이용하여 에지 맵을 얻는다. 에지 맵으로부터 3차원 물체의 각 면들을 분리하기 위해 레이블링 연산을 하고 각 면에서 중심점과 모서리 점들을 추출한다. 그 다음에, 평면 방정식으로부터 각 면이 평면인지 곡면인지를 판단한다. 3차원 물체를 표현하기 위해 각 면의 평면 또는 곡면의 계수 및 특징들을 추출한다. 합성영상과 실측영상을 통해서 제안된 기법의 성능을 알아보았고, 또한 제안된 기법으로 3차원 물체를 재구성하였다.

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Development of a Lane Detect Algorithm from Road-Facing Cameras on a Vehicle (차량에 부착된 측하방 CCD카메라를 이용한 차선추출 알고리즘 개발)

  • Rhee, Soo-Ahm;Lee, Tae-Yoon;Kim, Tae-Jung;Sung, Jung-Gon
    • Journal of Korean Society for Geospatial Information Science
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    • v.13 no.3 s.33
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    • pp.87-94
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    • 2005
  • 3D positional information of lane can be automatically calculated tv combining GPS data, IMU data if coordinates of lane centers are given. The Road Safety Survey and Analysis Vehicle(RoSSAV) is currently under development to analyze three dimensional safety and stability of roads. RoSSAV has GPS and IMU sensors to get positional information of the vehicle and two road-facing CCD cameras for extraction of lane coordinates. In this paper, we develop technology that automatically detects centers of lanes from the road-facing cameras of RoSSAV. The proposed algorithm defines line-support regions by grouping pixels with similar edge orientation and magnitude together and extracts a line from each line support region by planar fitting. Then if extracted lines and the region in-between satisfy the criteria of brightness and width, we decide this region as lane. The proposed algorithm was more precise and stable than the previously proposed algorithm based on brightness threshold method. Experiments with real road scenes confirmed that lane was effectively extracted by the proposed algorithm.

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Real-Time Gesture Recognition Using Boundary of Human Hands from Sequence Images (손의 외곽선 추출에 의한 실시간 제스처 인식)

  • 이인호;박찬종
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 1999.11a
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    • pp.438-442
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    • 1999
  • 제스처 인식은 직관적일 뿐 아니라, 몇 가지의 기본 구성요소에 의하여 코드화(code)가 용이하여, 인간과 컴퓨터의 상호작용(HCI, Human-Computer Interaction)에 있어서 폭넓게 사용되고 있다. 본 논문에서는 손의 모양이나 크기와 같은 개인차 및 조명의 변화나 배율과 같은 입력환경의 영향을 최소화하여, 특별한 초기화 과정이나 모델의 준비과정 없이도 제스처를 인식할 수 있고, 적은 계산량으로 실시간 인식이 가능한 제스처 인식 시스템의 개발을 목표로 한다. 본 논문에서는 손에 부착하는 센서나 마커 없이, CCD 카메라에 의하여 입력된 컬러영상에서, 컬러정보 및 동작정보를 이용하여 손영역을 추출하고, 추출된 손의 경계선 정보를 이용하여 경계선-중심 거리 함수를 생성했다. 그리고, 손가락의 끝 부분에서는 경계선-중심 거리가 극대점을 이룬다는 원리를 이용하여 생성된 함수의 주파수를 분석하여 극대점을 구함으로써 각각의 손가락 끝 위치를 찾고, 손의 자세를 인식하여 제스처를 인식했다. 또한 본 논문에서 제안된 제스처 인식 방법은 PC상에서 구현되어 그 유용성과 실효성이 증명되었다.

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Tracking Algorithm For Golf Swing Using the Information of Pixels and Movements (화소 및 이동 정보를 이용한 골프 스윙 궤도 추적 알고리즘)

  • Lee, Hong, Ro;Hwang, Chi-Jung
    • The KIPS Transactions:PartB
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    • v.12B no.5 s.101
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    • pp.561-566
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    • 2005
  • This paper presents a visual tracking algorithm for the golf swing motion analysis by using the information of the pixels of video frames and movement of the golf club to solve the problem fixed center point in model based tracking method. The model based tracking method use the polynomial function for trajectory displaying of upswing and downswing. Therefore it is under the hypothesis of the no movement of the center of gravity so this method is not for the amateurs. we proposed method using the information of pixel and movement, we first detected the motion by using the information of pixel in the frames in golf swing motion. Then we extracted the club head and hand by a properties of club shaft that consist of the parallel line and the moved location of club in up-swing and down-swing. In addition, we can extract the center point of user by tracking center point of the line between center of head and both foots. And we made an experiment with data that movement of center point is big. Finally, we can track the real trajectory of club head, hand and center point by using proposed tracking algorithm.

Rotation and Scale Invariant Face Detection Using Log-polar Mapping and Face Features (Log-polar변환과 얼굴특징추출을 이용한 크기 및 회전불변 얼굴인식)

  • Go Gi-Young;Kim Doo-Young
    • Journal of the Institute of Convergence Signal Processing
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    • v.6 no.1
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    • pp.15-22
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    • 2005
  • In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

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Object-Based Integral Imaging Depth Extraction Using Segmentation (영상 분할을 이용한 객체 기반 집적영상 깊이 추출)

  • Kang, Jin-Mo;Jung, Jae-Hyun;Lee, Byoung-Ho;Park, Jae-Hyeung
    • Korean Journal of Optics and Photonics
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    • v.20 no.2
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    • pp.94-101
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    • 2009
  • A novel method for the reconstruction of 3D shape and texture from elemental images has been proposed. Using this method, we can estimate a full 3D polygonal model of objects with seamless triangulation. But in the triangulation process, all the objects are stitched. This generates phantom surfaces that bridge depth discontinuities between different objects. To solve this problem we need to connect points only within a single object. We adopt a segmentation process to this end. The entire process of the proposed method is as follows. First, the central pixel of each elemental image is computed to extract spatial position of objects by correspondence analysis. Second, the object points of central pixels from neighboring elemental images are projected onto a specific elemental image. Then, the center sub-image is segmented and each object is labeled. We used the normalized cut algorithm for segmentation of the center sub-image. To enhance the speed of segmentation we applied the watershed algorithm before the normalized cut. Using the segmentation results, the subdivision process is applied to pixels only within the same objects. The refined grid is filtered with median and Gaussian filters to improve reconstruction quality. Finally, each vertex is connected and an object-based triangular mesh is formed. We conducted experiments using real objects and verified our proposed method.