• Title/Summary/Keyword: 가우시언 혼합 모델(GMM)

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IR Image Segmentation using GrabCut (GrabCut을 이용한 IR 영상 분할)

  • Lee, Hee-Yul;Lee, Eun-Young;Gu, Eun-Hye;Choi, Il;Choi, Byung-Jae;Ryu, Gang-Soo;Park, Kil-Houm
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.2
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    • pp.260-267
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    • 2011
  • This paper proposes a method for segmenting objects from the background in IR(Infrared) images based on GrabCut algorithm. The GrabCut algorithm needs the window encompassing the interesting known object. This procedure is processed by user. However, to apply it for object recognition problems in image sequences. the location of window should be determined automatically. For this, we adopted the Otsu' algorithm for segmenting the interesting but unknown objects in an image coarsely. After applying the Otsu' algorithm, the window is located automatically by blob analysis. The GrabCut algorithm needs the probability distributions of both the candidate object region and the background region surrounding closely the object for estimating the Gaussian mixture models(GMMs) of the object and the background. The probability distribution of the background is computed from the background window, which has the same number of pixels within the candidate object region. Experiments for various IR images show that the proposed method is proper to segment out the interesting object in IR image sequences. To evaluate performance of proposed segmentation method, we compare other segmentation methods.