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검색결과 383건 처리시간 0.024초

주변 전경 픽셀 전파 알고리즘 기반 실시간 이동 객체 검출 (A Real-time Motion Object Detection based on Neighbor Foreground Pixel Propagation Algorithm)

  • 응웬탄빈;정선태
    • 대한전자공학회논문지SP
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    • 제47권1호
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    • pp.9-16
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    • 2010
  • 이동 객체 검출은 입력 영상에서 배경과 다른 전경 객체를 찾는 것을 말하는 것으로 지능 영상 감시, HCI, 객체 기반 영상 압축 등의 여러 영상 처리 응용 분야에서 필요한 과정이다. 기존의 이동 객체 검출 알고리즘은 상당한 계산량을 요구하여 다채널 영상 감시 응용, 또는 임베디드 시스템에서의 단일 채널의 실시간 응용에 사용하는 데 애로가 많다. 보다 정확한 이동 객체 검출을 위하여 필요한 과정인 전경 마스크 정정은 보통 열림, 닫힘 등의 모폴로지 연산을 통해 수행된다. 모폴로지 연산은 계산량이 적지 않고 게다가 프로세싱 방법이 달라 이동 객체 검출의 다음 단계인 연결 요소 레이블링 루틴과 동시에 처리되기 어렵다. 본 논문에서는 먼저 모폴로지 연산과는 달리 연결 요소 레이블링 루틴에서 사용되는 주변 픽셀 점검 과정을 활용한 전경 마스크 정정 알고리즘인 "주변 전경 픽셀 전파"을 고안하고, 이를 활용하여 전경 마스크 정정과 연결 요소 레이블링이 동시에 수행될 수 있는 이동 객체 검출 방법을 제안한다. 실험을 통해, 제안된 이동 객체 검출 방법이 기존의 모폴로지 연산을 사용한 방법 보다 정확하게 이동 객체를 검출하였으며, 대상 실험 영상 프레임 및 비디오에 대해서는 최소 4배 이상 신속하게 처리됨을 확인하였다.

선택적 히스토그램 빈 기반 열화상 영상 전경 추출 (Foreground Extraction in Thermal Videos Based on Selective Histogram Bins)

  • 유광현;자히르;김진영;신도성
    • 디지털콘텐츠학회 논문지
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    • 제19권4호
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    • pp.757-770
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    • 2018
  • 열화상 영상기반 감시 시스템에서 전경추출은 매우 중요한 단계이다. 전경추출단계는 계산시간과 메모리 사용측면에서 시스템의 실시간 처리가 매우 효율적이어야 한다. 그러나 이러한 효율성은 ROI 탐지의 정확도와 매우 연관되어 있다. 본 논문에서 열화상 비디오 처리를 위하여 새로운 히스토그램 빈에 기반하여 배경과 전경을 분리하기 위한 두 가지 방법을 제시하는데, 이는 임의의 주어진 환경에서 열화상영상의 시간상에서 일관성을 갖는 다는 점과, 이러한 성질이, 간단한 시간축 메디안 필터링에 비하여 80%이상의 메모리를 절감할 수 있다.

동적 배경에서의 고밀도 광류 기반 이동 객체 검출 (Dense Optical flow based Moving Object Detection at Dynamic Scenes)

  • 임효진;최연규;구엔 칵 쿵;정호열
    • 대한임베디드공학회논문지
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    • 제11권5호
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    • pp.277-285
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    • 2016
  • Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

Probing Cosmic Near Infrared Background using AKARI Data

  • 서현종;;정웅섭;이형목;;;;표정현
    • 천문학회보
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    • 제38권1호
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    • pp.34.1-34.1
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    • 2013
  • The first generation stars in the universe are not observed as discrete objects by using current observational facilities, but their contributions are redshifted to the near infrared wavelength bands at present universe. Therefore, investigation of background radiation at near infrared is important for the study of the first stars. In this study, we present new observations of spatial fluctuations in sky brightness toward the north ecliptic pole using data from AKARI. Among pointed observation program of AKARI, we used two pointing surveys named Monitor field and NEP wide field at three wavelength bands 2.4, 3.2, and 4.1 ${\mu}m$. To obtain spatial fluctuations from observed images, first of all, we exclude pixels affected by resolved foreground objects and then obtain diffuse map which consists of diffused radiation only. Because the diffuse map contains not only cosmological components but also various foreground components, in order to detect cosmological components, we estimate the contributions of foreground components separately. The results of this study show that there remains excess spatial fluctuation that cannot be explained by known foreground sources. This work is based on observations with AKARI, a JAXA project with the participation of ESA.

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Probing Cosmic Near Infrared Background using AKARI Data

  • 서현종;;정웅섭;이형목;;;;표정현
    • 천문학회보
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    • 제38권1호
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    • pp.35.1-35.1
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    • 2013
  • The first generation stars in the universe are not observed as discrete objects by using current observational facilities, but their contributions are redshifted to the near infrared wavelength bands at present universe. Therefore, investigation of background radiation at near infrared is important for the study of the first stars. In this study, we present new observations of spatial fluctuations in sky brightness toward the north ecliptic pole using data from AKARI. Among pointed observation program of AKARI, we used two pointing surveys named Monitor field and NEP wide field at three wavelength bands 2.4, 3.2, and 4.1 ${\mu}$. To obtain spatial fluctuations from observed images, first of all, we exclude pixels affected by resolved foreground objects and then obtain diffuse map which consists of diffused radiation only. Because the diffuse map contains not only cosmological components but also various foreground components, in order to detect cosmological components, we estimate the contributions of foreground components separately. The results of this study show that there remains excess spatial fluctuation that cannot be explained by known foreground sources. This work is based on observations with AKARI, a JAXA project with the participation of ESA.

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연속적인 배경 모델 학습을 이용한 코드북 기반의 전경 추출 알고리즘 (Codebook-Based Foreground Extraction Algorithm with Continuous Learning of Background)

  • 정재영
    • 디지털콘텐츠학회 논문지
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    • 제15권4호
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    • pp.449-455
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    • 2014
  • 이동 물체의 검출은 비디오 감시, 보행자의 행동 분석과 같은 컴퓨터 시각 분야에서 매우 중요한 전처리 작업이다. 이는 실제 외부 환경을 대상으로 할 때, 영상 시퀀스에 존재하는 배경의 불규칙한 움직임, 조명 변화, 그림자, 배경 물체의 위상 변화 및 잡음 등으로 인하여 매우 어려운 작업이다. 본 논문에서는 코드북 기반의 전경 검출 알고리즘을 제안한다. 코드북은 입력 영상으로부터 얻어지는 배경화소에 대한 정보 데이터베이스이다. 먼저, 첫 번째 프레임을 배경 영상으로 가정하고 이를 입력 영상과 비교하여 차 영상을 구한다. 구해진 차 영상에는 순수한 이동 물체뿐만 아니라, 잡음까지 포함된다. 둘째로, 전경으로 검출된 화소의 색상과 밝기 값을 가지고 코드북을 조사하여 존재하는 경우 잘못 추출된 전경 화소로 판단하고 전경에서 제거한다. 마지막으로, 다음번 입력되는 프레임을 반복 처리하기 위하여 배경 영상을 새롭게 갱신하는데, 배경 화소로 검출된 화소의 경우에는 현재의 입력 영상으로부터 추정되며, 전경 화소로 검출된 경우에는 이전 배경 영상의 화소 값을 복사하여 사용한다. 제안한 알고리즘을 PETS2009 데이터에 적용한 결과를 GMM 알고리즘과 표준 코드북 알고리즘의 결과와 비교하여 보인다.

2D 이미지에서 3D 모델링 데이터 변환 알고리즘에 관한 연구 (Study on the 3D Modeling Data Conversion Algorithm from 2D Images)

  • 최태준;이희만;김응수
    • 한국멀티미디어학회논문지
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    • 제19권2호
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    • pp.479-486
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    • 2016
  • In this paper, the algorithm which can convert a 2D image into a 3D Model will be discussed. The 2D picture drawn by a user is scanned for image processing. The Canny algorithm is employed to find the contour. The waterfront algorithm is proposed to find foreground image area. The foreground area is segmented to decompose the complex shapes into simple shapes. Then, simple segmented foreground image is converted into 3D model to become a complex 3D model. The 3D conversion formular used in this paper is also discussed. The generated 3D model data will be useful for 3D animation and other 3D contents creation.

FOREGROUND OF GAMMA-RAY BURSTS (GRBS) FROM AKARI FIS DATA

  • Toth, L. Viktor;Doi, Yasuo;Zahorecz, Sarolta;Agas, Marton;Balazs, Lajos G.;Forro, Adrienn;Racz, Istvan I.
    • 천문학논총
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    • 제32권1호
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    • pp.113-116
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    • 2017
  • A significant number of the parameters of a gamma-ray burst (GRB) and its host galaxy are calculated from the afterglow. There are various methods obtaining extinction values for the necessary correction for galactic foreground. These are: galaxy counts, from HI 21 cm surveys, from spectroscopic measurements and colors of nearby Galactic stars, or using extinction maps calculated from infrared surveys towards the GRB. We demonstrate that AKARI Far-Infrared Surveyor sky surface brightness maps are useful uncovering the fine structure of the galactic foreground of GRBs. Galactic cirrus structures of a number of GRBs are calculated with a 2 arcminute resolution, and the results are compared to that of other methods.

Faraday Rotation Measurein the Large-Scale Structure II

  • Akahori, Takuya;Ryu, Dong-Su
    • 천문학회보
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    • 제35권1호
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    • pp.83.1-83.1
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    • 2010
  • In the last meeting of KAS, we reported the first statistical study of Faraday rotation measure (RM) in the large-scale structure of the universe using the data of cosmological structure formation simulations. With a turbulence dynamo model for the intergalactic magnetic field (IGMF), we predicted that the root mean square of RM through filaments is \sim 1 rad/m^2. Future radio observatories such as the Square Kilometer Array (SKA) could detect this signal level. However, it is known that the typical foreground galactic RM is a few tens and less than ten rad/m^2 in the low and high galactic latitudes, respectively. So the RM in the large-scale structure could be detected only after the foreground galactic RM is removed. In this talk, we show how we remove the foreground galactic RM and what we obtain from the masked data, by using some noise models and masking techniques. Our results can be used to simulate future RM observations by SKA, and eventually to constrain the origin and evolution of the IGMF in the large-scale structure.

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개선된 다중 구간 샘플링 배경제거 알고리즘 (An Improved Multiple Interval Pixel Sampling based Background Subtraction Algorithm)

  • 무하마드 타릭 마흐무드;최영규
    • 반도체디스플레이기술학회지
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    • 제18권3호
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    • pp.1-6
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    • 2019
  • Foreground/background segmentation in video sequences is often one of the first tasks in machine vision applications, making it a critical part of the system. In this paper, we present an improved sample-based technique that provides robust background image as well as segmentation mask. The conventional multiple interval sampling (MIS) algorithm have suffer from the unbalance of computation time per frame and the rapid change of confidence factor of background pixel. To balance the computation amount, a random-based pixel update scheme is proposed and a spatial and temporal smoothing technique is adopted to increase reliability of the confidence factor. The proposed method allows the sampling queue to have more dispersed data in time and space, and provides more continuous and reliable confidence factor. Experimental results revealed that our method works well to estimate stable background image and the foreground mask.