• Title, Summary, Keyword: Mask Video

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A Study on an Image Noise Erase Method By to be an Image Noise Frequent Occur for Raining, in Measurement Machine Vision System for using CCD Camera Of Pantograph Sliding Plate Abrasion (판타그라프 습판마모의 머신비젼 측정에서 우천시 발생하는 영상의 노이즈 제거방법에 관한 연구)

  • Lee, Seong-Gwon;Lee, Dae-Won;Kim, Gil-Dong;Oh, Sang-Yoon;Kim, Seong-Min
    • Proceedings of the KSR Conference
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    • pp.872-898
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    • 2007
  • Pantograph sliding plate abrasion auto-detect system, one of the electric rail car auto-detecting devices, is a system that decides how much abrasion and when to replace without an inspector physically looking at the abrasion on the wet plate using machine vision, a cutting-edge technology. This paper covers the cause of deteriorating reliability that affects pantograph wet plate edge detection due to noise added to the video when it rains. In order to remove such noise, problems should be checked through Smoothing, Averaging mask and Median filter using filtering technique and stable edge detection without being affected by noise should be induced in video measurement used in machine vision technology.

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Object Store Method for Interactive Multimedia Broadcasting (대화형 멀티미디어 방송을 위한 객체 저장 방법)

  • Han, Dae-Young;Hwang, Bu-Hyun;Kim, Dae-In;Kim, Jae-In;Na, Choul-Su
    • The Journal of the Korea Contents Association
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    • v.9 no.2
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    • pp.51-59
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    • 2009
  • Interactive multimedia broadcasting can serve various additional information of object in multimedia because of the commercialized data broadcasting by communication and broadcasting convergence. One of the most important factors in interactive multimedia broadcasting is User-Centric Interoperability. The higher User-Centric Interoperability, the more information of user-interest objects are served quickly by user request. This proposed method finds own area of the object in mask video and divides the area into equal parts. And then it store as a form of bitsum after clustering the area. As a result of experiment, We confirm the method is efficient to use space for storing position information of the object.

An Automatic Segmentation Method for Video Object Plane Generation (비디오 객체 생성을 위한 자동 영상 분할 방법)

  • 최재각;김문철;이명호;안치득;김성대
    • Journal of Broadcast Engineering
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    • v.2 no.2
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    • pp.146-155
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    • 1997
  • The new video coding standard Iv1PEG-4 is enabling content-based functionalities. It requires a prior decomposition of sequences into video object planes (VOP's) so that each VOP represents moving objets. This paper addresses an image segmentation method for separating moving objects from still background (non-moving area) in video sequences using a statistical hypothesis test. In the proposed method. three consecutive image frames are exploited and a hypothesis testing is performed by comparing two means from two consecutive difference images. which results in a T-test. This hypothesis test yields a change detection mask that indicates moving areas (foreground) and non-moving areas (background), Moreover. an effective method for extracting

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전자총 히터(electron gun heater) 자동검사를 위한 머신비젼 알고리즘

  • 김인수;이문규
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.3
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    • pp.58-67
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    • 2000
  • Electron gun heaters are used to heat a cathode in video(TV) monitors. Major defects of the electron gun heaters include dimensional inaccuracy and pollution with dirty materials. In this paper, to save the labor and time being taken to inspect the heaters, a machine vision system is considered. For the system, a new algorithm is developed to measure the 9 different dimensions of each heater and to detect polluted defects. The algorithm consists of three stages. In the first stage, the center of the heater image is obtained and then its boundary detection is performed. For the efficient boundary detection, a mask called the sum mask is used. In the second stage of the algorithm, a set of fiducial points are determined on the boundary image. Finally, using the fiducial points specified dimensions are measured and the amount of polluted area is computed in the third stage. The performance of the algorithm is evaluated for a set of real specimens. The results indicate that measurements obtained by the algorithm satisfy the tolerance limits fur most of the dimensions and the algorithm detects the polluted defects successfully.

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Separation of Occluding Pigs using Deep Learning-based Image Processing Techniques (딥 러닝 기반의 영상처리 기법을 이용한 겹침 돼지 분리)

  • Lee, Hanhaesol;Sa, Jaewon;Shin, Hyunjun;Chung, Youngwha;Park, Daihee;Kim, Hakjae
    • Journal of Korea Multimedia Society
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    • v.22 no.2
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    • pp.136-145
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    • 2019
  • The crowded environment of a domestic pig farm is highly vulnerable to the spread of infectious diseases such as foot-and-mouth disease, and studies have been conducted to automatically analyze behavior of pigs in a crowded pig farm through a video surveillance system using a camera. Although it is required to correctly separate occluding pigs for tracking each individual pigs, extracting the boundaries of the occluding pigs fast and accurately is a challenging issue due to the complicated occlusion patterns such as X shape and T shape. In this study, we propose a fast and accurate method to separate occluding pigs not only by exploiting the characteristics (i.e., one of the fast deep learning-based object detectors) of You Only Look Once, YOLO, but also by overcoming the limitation (i.e., the bounding box-based object detector) of YOLO with the test-time data augmentation of rotation. Experimental results with two-pigs occlusion patterns show that the proposed method can provide better accuracy and processing speed than one of the state-of-the-art widely used deep learning-based segmentation techniques such as Mask R-CNN (i.e., the performance improvement over Mask R-CNN was about 11 times, in terms of the accuracy/processing speed performance metrics).

A Study on Image Restoration Filter in Impulse Noise Environments (임펄스 잡음 환경에서 영상복원 필터에 관한 연구)

  • Xu, Long;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.2
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    • pp.475-481
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    • 2014
  • As the society develops to advanced digital information times, many studies are underway about digital video processing technology areas such as image restoration. There are typical methods to restore the image which have been damaged by the impulse noise like SM(standard median) filter and CWM(center weighted median) filter. These filters show excellent noise reduction capabilities in low noise density areas, but in high noise density areas, noise reduction capabilities are not sufficient. In this paper, in order to restore the degraded images in impulse(Salt & Pepper) noise environment, the image restoration filter algorithm was suggested which expands and subdivide the mask focusing on damaged pixels. And to demonstrate the superiority of the proposed algorithm used PSNR (peak signal to noise ratio) as the standard of judgement.

High Density Impulse Noise Reduction Filter Algorithm using Effective Pixels (유효 화소를 이용한 고밀도 임펄스 잡음 제거 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.10
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    • pp.1320-1326
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    • 2018
  • Digital video equipment is important in the 4th industrial revolution and is widely used in different fields for various purpose. Data of digital video equipment is exposed to noise due to different reasons including user environment and processing and such noise affect output and processing method. This can even cause error, resulting in decreased reliability of the equipment. In this research, it offers algorithm to effectively recover video by removing noise and impulse noise occurring during the process of channel delivery. This proposed algorithm recovers video by exploring valid pixel using directional local mask and noise determination. Then, valid pixel calculated goes through the final output calculation through comparative analysis on estimation. For comparing suggested method and algorithm, simulation is carried out. For checking the function of it, PSNR and profile are analyzed.

Distance Measurement of the Multi Moving Objects using Parallel Stereo Camera in the Video Monitoring System (영상감시 시스템에서 평행식 스테레오 카메라를 이용한 다중 이동물체의 거리측정)

  • 김수인;이재수;손영우
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.18 no.1
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    • pp.137-145
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    • 2004
  • In this paper, a new algorithm for the segmentation of the multi moving objects at the 3 dimension space and the method of measuring the distance from the camera to the moving object by using stereo video monitoring system is proposed. It get the input image of left and right from the stereo video monitoring system, and the area of the multi moving objects segmented by using adaptive threshold and PRA(pixel recursive algorithm). Each of the object segmented by window mask, then each coordinate value and stereo disparity of the multi moving objects obtained from the window masks. The distance of the multi moving objects can be calculated by this disparity, the feature of the stereo vision system and the trigonometric function. From the experimental results, the error rate of a distance measurement be existed within 7.28%, therefore, in case of implementation the proposed algorithm, the stereo security system, the automatic moving robot system and the stereo remote control system will be applied practical application.

Video object segmentation using a novel object boundary linking (새로운 객체 외곽선 연결 방법을 사용한 비디오 객체 분할)

  • Lee Ho-Suk
    • The KIPS Transactions:PartB
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    • v.13B no.3
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    • pp.255-274
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    • 2006
  • Moving object boundary is very important for the accurate segmentation of moving object. We extract the moving object boundary from the moving object edge. But the object boundary shows broken boundaries so we develop a novel boundary linking algorithm to link the broken boundaries. The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundaries and searches for other terminating pixels to link in concentric circles clockwise within a search radius in the forward direction. The boundary linking algorithm guarantees the shortest distance linking. We register the background from the image sequence using the stationary background filtering. We construct two object masks, one object mask from the boundary linking and the other object mask from the initial moving object, and use these two complementary object masks to segment the moving objects. The main contribution of the proposed algorithms is the development of the novel object boundary linking algorithm for the accurate segmentation. We achieve the accurate segmentation of moving object, the segmentation of multiple moving objects, the segmentation of the object which has a hole within the object, the segmentation of thin objects, and the segmentation of moving objects in the complex background using the novel object boundary linking and the background automatically. We experiment the algorithms using standard MPEG-4 test video sequences and real video sequences of indoor and outdoor environments. The proposed algorithms are efficient and can process 70.20 QCIF frames per second and 19.7 CIF frames per second on the average on a Pentium-IV 3.4GHz personal computer for real-time object-based processing.

Segmentation and Tracking Algorithm for Moving Speaker in the Video Conference Image (화상회의 영상에서 움직이는 화자의 분할 및 추적 알고리즘)

  • Choi Woo-Young;Kim Han-Me
    • Journal of IKEEE
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    • v.6 no.1
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    • pp.54-64
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    • 2002
  • In this paper, we propose the algorithm for segmenting the moving speaker and tracking its movement in the video conference image. For real time processing, we simplify the algorithm which is processed in the order of the segmenting and the tracking step. In the segmenting step, the speaker object is segmented from the image by using both the motion information obtained from the difference method and the illuminance information of image. The reference mask image is created from segmented speaker object. In the tracking step, the moving speaker is tracked by using simple block matching algorithm of which computation time is reduced by discarding the blocks which are classified into the unuseful blocks. In the simulation, we can get the good result of segmenting and tracking the moving speaker by applying the proposed algorithm to several test images.

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