• Title/Summary/Keyword: Image Object

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Convergence Control of Moving Object using Opto-Digital Algorithm in the 3D Robot Vision System

  • Ko, Jung-Hwan;Kim, Eun-Soo
    • Journal of Information Display
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    • 제3권2호
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    • pp.19-25
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    • 2002
  • In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

JPEG-2000 Gradient-Based Coding: An Application To Object Detection

  • Lee, Dae Yeol;Pinto, Guilherme O.;Hemami, Sheila S.
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2013년도 추계학술대회
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    • pp.165-168
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    • 2013
  • Image distortions, such as quantization errors, can have a severe negative impact on the performance of computer vision algorithms, and, more specifically, on object detection algorithms. State-of-the-art implementations of the JPEG-2000 image coder commonly allocate the available bits to minimize the Mean-Squared-Error (MSE) distortion between the original image and the resulting compressed image. However, considering that some state-of-the-art object detection methods use the gradient information as the main image feature, an improved object detection performance is expected for JPEG-2000 image coders that allocate the available bits to minimize the distortions on the gradient content. Accordingly, in this work, the Gradient Mean-Squared-Error (GMSE) based JPEG-2000 coder presents an improved object detection performance over the MSE based JPEG-2000 image coder when the object of interest is located at the same spatial location of the image regions with the strongest gradients and also for high bit-rates. For low bit-rates (e.g. 0.07bpp), the GMSE based JPEG-2000 image coder becomes overly selective in choosing the gradients to preserve, and, as a result, there is a greater chance of mismatch between the spatial locations of the gradients that the coder is trying to preserve and the spatial locations of the objects of interest.

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Specified Object Tracking Problem in an Environment of Multiple Moving Objects

  • Park, Seung-Min;Park, Jun-Heong;Kim, Hyung-Bok;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제11권2호
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    • pp.118-123
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    • 2011
  • Video based object tracking normally deals with non-stationary image streams that change over time. Robust and real time moving object tracking is considered to be a problematic issue in computer vision. Multiple object tracking has many practical applications in scene analysis for automated surveillance. In this paper, we introduce a specified object tracking based particle filter used in an environment of multiple moving objects. A differential image region based tracking method for the detection of multiple moving objects is used. In order to ensure accurate object detection in an unconstrained environment, a background image update method is used. In addition, there exist problems in tracking a particular object through a video sequence, which cannot rely only on image processing techniques. For this, a probabilistic framework is used. Our proposed particle filter has been proved to be robust in dealing with nonlinear and non-Gaussian problems. The particle filter provides a robust object tracking framework under ambiguity conditions and greatly improves the estimation accuracy for complicated tracking problems.

RELATIONSHIP BETWEEN ERROR DIFFUSION COEFFICIENTS, OBJECT SIZE AND OBJECT POSITION FOR CGH

  • Nishi, Susumu;Tanaka, Ken-ichi
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.492-497
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    • 2009
  • Computer-Generated Hologram (CGH) is made for three dimensional image of a virtual object. Error diffusion method is used for the phase quantization of CGH, and it is known to be effective to the image quality improvement of the reconstructed image. However, the image quality of the reconstructed image from the CGH using error diffusion method depends on the selection of error diffusion coefficient. In this paper, we derived the relational expression to obtain the error diffusion coefficient from the position of the input object and size of the input object for CGH. As a result, the method of this thesis was able to obtain an excellent reconstructed image compared with the case to derive the error diffusion coefficient from only the position of the input image.

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라돈 변환을 이용한 회전된 물체의 효율적인 보정 (Efficient Correction of a Rotated Object Using Radon Transform)

  • 조보호;정성환
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제14권3호
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    • pp.291-295
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    • 2008
  • 본 논문은 비전 시스템을 통하여 입력되어 들어오는 회전된 물체를 보정하기 위해 사용하는 선 구조 분석 도구인 라돈변환의 문제점을 해결하기 위해 입력 영상 간소화 방법을 제안한다. 먼저, 비전 시스템을 통하여 입력된 영상 내에서 불필요한 배경 부분을 제거하여 물체 영상을 추출한다. 다음, 추출된 물체 영상에 대하여 기울기를 고려하여 제한된 물체 영상만을 라돈 변환의 최종 입력 영상으로 추출한다. 마지막으로 최종 입력 영상에 대하여 라돈 변환을 사용하여 회전각을 추출한 후, 원 영상 내의 회전된 물체를 보정한다. 실험 결과, 제안한 방법은 처리 속도를 약 64% 향상시킬 수 있었고, 기억용량은 약 18% 줄일 수 있었으며, 선 검출율은 약 18%까지 향상시킬 수 있었다.

복합초점함수의 시간열 영상적용을 통한 3 차원정보복원에 관한 연구 (Research for 3-D Information Reconstruction by Appling Composition Focus Measure Function to Time-series Image)

  • 김정길;한영준;한헌수
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2004년도 추계학술대회 논문집
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    • pp.426-429
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    • 2004
  • To reconstruct the 3-D information of a irregular object, this paper proposes a new method applying the composition focus measure to time-series image. A focus measure function is carefully selected because a focus measure is apt to be affected by the working environment and the characteristics of an object. The proposed focus measure function combines the variance measure which is robust to noise and the Laplacian measure which, regardless of an object shape, has a good performance in calculating the focus measure. And the time-series image, which considers the object shape, is proposed in order to efficiently applying the interesting window. This method, first, divides the image frame by the window. Second, the composition focus measure function be applied to the windows, and the time-series image is constructed. Finally, the 3-D information of an object is reconstructed from the time-series images considering the object shape. The experimental results have shown that the proposed method is suitable algorithm to 3-D reconstruction of an irregular object.

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깊이와 칼라 영상의 특징을 사용한 ROI 기반 객체 추출 (ROI Based Object Extraction Using Features of Depth and Color Images)

  • 류가애;장호욱;김유성;류관희
    • 한국콘텐츠학회논문지
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    • 제16권8호
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    • pp.395-403
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    • 2016
  • 최근 들어 영상처리는 여러 분야에서 사용되어지고 있다. 영상처리에서 많이 연구되어지고 있는 기술은 실시간으로 객체를 추적하는 기술이다. 객체를 추적하는 방법은 보행자를 추적하는 HOG(Histogram of Oriented Gradients), 전경과 배경 분리 방법을 사용하는 Codebook 같은 방법 들이 많이 알려져 있다. 그러나 객체가 움직이거나 동적인 배경, 조명변화가 심할 경우 객체 추출이 어려워진다. 본 논문에서는 ROI(Region of Interest)기반 깊이영상과 컬러영상의 특징을 이용해 객체를 추출하는 방법을 제안한다. 첫 번째, 깊이 영상에서 배경분리를 통해 객체의 위치를 찾아 ROI로 설정해준다. 두 번째, 컬러영상을 이용하여 영상의 특징점을 찾는다. 세 번째, 특징점과 객체의 볼록헐(convex hull) 구성점들을 이용하여 새로운 윤곽을 만들어 더 정확한 객체를 추출하도록 한다. 마지막으로 본 논문에서 제안한 방법과 기존 방법과의 비교를 통해 제안한 방법의 결과가 좀 더 정확한 객체를 추출하고 있음을 검증하였다.

퍼지 클러스터링과 스트링 매칭을 통합한 형상 인식법 (Pattern Recognition Method Using Fuzzy Clustering and String Matching)

  • 남원우;이상조
    • 대한기계학회논문집
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    • 제17권11호
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    • pp.2711-2722
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    • 1993
  • Most of the current 2-D object recognition systems are model-based. In such systems, the representation of each of a known set of objects are precompiled and stored in a database of models. Later, they are used to recognize the image of an object in each instance. In this thesis, the approach method for the 2-D object recognition is treating an object boundary as a string of structral units and utilizing string matching to analyze the scenes. To reduce string matching time, models are rebuilt by means of fuzzy c-means clustering algorithm. In this experiments, the image of objects were taken at initial position of a robot from the CCD camera, and the models are consturcted by the proposed algorithm. After that the image of an unknown object is taken by the camera at a random position, and then the unknown object is identified by a comparison between the unknown object and models. Finally, the amount of translation and rotation of object from the initial position is computed.

어류객체 추출을 위한 영상분할 알고리즘 (Image Segmentation Algorithm for Fish Object Extraction)

  • 안홍수;오정수
    • 한국정보통신학회논문지
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    • 제14권8호
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    • pp.1819-1826
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    • 2010
  • 본 논문은 어류영상 검색을 위해 어류영상에서 어류객체를 추출하기 위한 영상분할 알고리즘을 제안하고 있다. 명암 유사도를 이용한 기존 알고리즘은 객체와 배경의 명암이 유사한 경계 영역에서 잘못된 영상분할 결과를 초래한다. 제안된 알고리즘은 대비가 약한 경계영역에 대응하기 위해 강화된 에지와 적응적 블록단위의 임계값을 사용하고, 대비가 없는 경계 영역에서 침식 혹은 단절된 객체를 개선하기 위해 가상 객체를 사용하고 있다. 모의실험 결과는 시각적으로 좋은 어류객체를 추출하는 비율이 기존 알고리즘에서는 90% 이하인 반면 제안된 알고리즘에서는 97.7%인 것을 보여주고 있다.

Measurement of 3-D range-image of object diagnolly moving against semiconductor laser light beam

  • Shinohara, Shigenobu;Ichioka, Yoshiyuki;Ikeda, Hiroaki;Yoshida, Hirofumi;Sumi, Masao
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.299-302
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    • 1995
  • Recently, we proposed a 3-D range-image measuring system for a slowly moving object by mechanically scanning a laser light beam emitted from a self mixing laser diode. In this paper, we introduced that every object moves along a straight line course, which is set diagonally against the semiconductor laser beam so that we can recognize each shape and size parameters of objects separately from the acquired 3-D range-image. We measured a square mesa on a square plane as an object. The measured velocity was 4.44mm/s and 4.63mm/s with an error of 0.56mm/s to 0.37mm/s. And thickness error of the mesa was 0.5mm to 0.6mm, which was obtained from the 3-D range-image of the standstill or moving object with thickness of 17.Omm.

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