• Title/Summary/Keyword: moving image

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A Study on External Light Noise Reduction Using Stereo Vision System in Image Monitoring System (스테레오비전시스템을 이용한 실내 영상감시시스템의 외란광 간섭 경감에 관한 연구)

  • Kim, Soo-In
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.9
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    • pp.83-90
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    • 2009
  • In this paper, a method for reduction of error ratio by external light noise is proposed, which separates error moving component caused by external light noise from moving component of an object, using depth information of stereo image. If measured depth information change of extracted moving component is insignificant, the moving component is considered as external light noise, which concludes that there is no moving object. Experimental results assert the usefulness of the proposed method which makes error ratios by external light noise and by false image as shadow diminish.

Boundary Line Extract for Moving Object Tracking (이동 물체 추적을 위한 경계선 추출)

  • Kim, Tea-Sik;Lee, Ju-Shin
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.2
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    • pp.28-34
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    • 1998
  • In this paper, I'd like to make a suggestion for boundary line detect algorithm which is used 3-D image processing system in order to track moving object. Through this study, more than anything else, difference image method was adopted to detect moving object in input image. To detect moving object, I made use of detect windows constructed by 4's predictive areas and object area for the purpose of reducing processing time and its size was determined by the size of moving object and prediction parameter directed center position. And also, tracking camera was movable toward the direction of X, Y by DC motor. As a conclusion of the study proposed algorithm, I found out the following results that tracking error was less than 6% of total moving object size and maximum tracking time 2 seconds by toy-car simulation.

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Recognition of Moving Objects in Mobile Robot with an Omnidirectional Camera (전방위카메라를 이용한 이동로봇에서의 이동물체 인식)

  • Kim, Jong-Cheol;Kim, Young-Myoung;Suga, Yasuo
    • The Journal of Korea Robotics Society
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    • v.3 no.2
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    • pp.91-98
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    • 2008
  • This paper describes the recognition method of moving objects in mobile robot with an omnidirectional camera. The moving object is detected using the specific pattern of an optical flow in omnidirectional image. This paper consists of two parts. In the first part, the pattern of an optical flow is investigated in omnidirectional image. The optical flow in omnidirectional image is influenced on the geometry characteristic of an omnidirectional camera. The pattern of an optical flow is theoretically and experimentally investigated. In the second part, the detection of moving objects is presented from the estimated optical flow. The moving object is extracted through the relative evaluation of optical flows which is derived from the pattern of optical flow. In particular, Focus-Of-Expansion (FOE) and Focus-Of-Contraction (FOC) vectors are defined from the estimated optical flow. They are used as reference vectors for the relative evaluation of optical flows. The proposed algorithm is performed in four motions of a mobile robot such as straight forward, left turn, right turn and rotation. Experimental results using real movie show the effectiveness of the proposed method.

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Segmentation of Moving Multiple Vehicles using Logic Operations (논리연산을 이용한 주행차량 영상분할)

  • Choi Kiho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.1 no.1
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    • pp.10-16
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    • 2002
  • In this paper, a novel algorithm for segmentation of moving multiple vehicles in video sequences using logic operations is proposed. For the case of multiple vehicles in a scene, the proposed algorithm begins with a robust double-edge image derived from the difference between two successive frames using exclusive OR operation. After extracting only the edges of moving multiple vehicles using Laplacian filter, AND operation and dilation operation, the image is segmented into moving multiple vehicle image. The features of moving vehicles can be directly extracted from the segmented images. The proposed algorithm has no the two preprocessing steps, so it can reduce noises which are norm at in preprocessing of the original images. The algorithm is more simplified using logic operations. The proposed algorithm is evaluated on an outdoor video sequence with moving multiple vehicles in 90,000 frames of 30fps by a low-end video camera and produces promising results.

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Lattice-Based Background Motion Compensation for Detection of Moving Objects with a Single Moving Camera (이동하는 단안 카메라 환경에서 이동물체 검출을 위한 격자 기반 배경 움직임 보상방법)

  • Myung, Yunseok;Kim, Gyeonghwan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.1
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    • pp.52-54
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    • 2015
  • In this paper we propose a new background motion compensation method which can be applicable to moving object detection with a moving monocular camera. To estimate the background motion, a series of image warpings are carried out for each pair of the corresponding patches, defined by the fixed-size lattice, based on the motion information extracted from the feature points surrounded by the patches and the estimated camera motion. Experiment results proved that the proposed has approximately 50% faster in execution time and 8dB higher in PSNR comparing to a conventional method.

A Tracking System of Moving Object using Active Blocks) (액티브 블록을 이용한 단일 이동 물체 추적 시스템)

  • 안인수;최태섭;김광훈;임승하;사공석진
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.37 no.3
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    • pp.21-29
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    • 2000
  • In this paper, we propose a way to detect a moving object efficiently and to track it using the active blocks. Instead of all Pixels in 8*8 Pixel value, any special pixel is extracted and we detect a moving object by comparison and by analysis the difference image information from darkness value of the same area. In the acquisition of image data by software processing, we reduce the number of data which obtain by convert high resolution image to low resolution image, and we can track a moving object in real time. So it can track a moving object in simple system without all the pixel value of the image data or additional VxD(Virtual x Driver). This system can be useful to track of a moving object in fixed block on PC(Personal Computer) and low custom.

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Estimation of Vehicle Traveling Speed Using Moving Image (동영상을 이용한 주행차량속도 산정)

  • 이종출;장호식;강상민;박규열
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2003.10a
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    • pp.187-192
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    • 2003
  • of the road would be a key index judged for a safety at the vehicle driving on the road. In Korea, as seen through a lot of documents, the vehicle driving speed is much faster compared with the design speed. The vehicle driving speed is an important element to get to know the vehicle driving characteristics. However, it is not easy to obtain the vehicle driving speed relating to vehicles' consecutive movements just merely through the presently used methods of vehicle driving speed. In consequence, this study has conducted photographing vehicle movements by use of digital moving images. Based on digital moving Images pictured, we have obtained a certain time interval frame and extracted out vehicles' coordinates and calculated vehicle speed from the firstly rectified image and the secondly rectified image. We could obtain comparatively exact results in the calculation of vehicle driving speed as errors of about 4%, as a result of comparison and verification of vehicle speed calculated from the digital moving images and the speed obtained from DGPS.

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The Study of automatic region segmentation method for Non-rigid Object Tracking (Non-rigid Object의 추적을 위한 자동화 영역 추출에 관한 연구)

  • 김경수;정철곤;김중규
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.183-186
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    • 2001
  • This paper for the method that automatically extracts moving object of the video image is presented. In order to extract moving object, it is that velocity vectors correspond to each frame of the video image. Using the estimated velocity vector, the position of the object are determined. the value of the coordination of the object is initialized to the seed, and in the image plane, the moving object is automatically segmented by the region growing method and tracked by the range of intensity and information about Position. As the result of an application in sequential images, it is available to extract a moving object.

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Tracking of a Moving Target Using the Accumulated Ultrasonic Image (초음차 응답 누적영상을 이용한 이동물체 추적)

  • Han, Moon-Yong;Hahn, Hern-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.2
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    • pp.164-172
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    • 2000
  • To follow a moving target keeping a certain distance it is essential for a mobile robot to detect the target first and to measure its pose and velocity. This paper proposes a new solution for this problem using the accumulated ultrasonic image which is constructed by accumulating the returned ultrasonic signal along the time axis for a certain number of measurement periods. A moving target is separated by selecting the trajectory whose inclination is different from others in the imag since the inclination of a trajectory represents the relative speed of the target against the mobile robot. The proposed algorithm was implemented on a mobile robot and has shown that the robot follows a moving target successfully.

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Moving Object Edge Extraction from Sequence Image Based on the Structured Edge Matching (구조화된 에지정합을 통한 영상 열에서의 이동물체 에지검출)

  • 안기옥;채옥삼
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.425-428
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    • 2003
  • Recently, the IDS(Intrusion Detection System) using a video camera is an important part of the home security systems which start gaining popularity. However, the video intruder detection has not been widely used in the home surveillance systems due to its unreliable performance in the environment with abrupt illumination change. In this paper, we propose an effective moving edge extraction algorithm from a sequence image. The proposed algorithm extracts edge segments from current image and eliminates the background edge segments by matching them with reference edge list, which is updated at every frame, to find the moving edge segments. The test results show that it can detect the contour of moving object in the noisy environment with abrupt illumination change.

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