International Journal of Contents

  • 제9권1호
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  • Pages.6-10
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  • 2013
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  • 1738-6764(pISSN)
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  • 2093-7504(eISSN)
한국콘텐츠학회 (The Korea Contents Association)
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Unconstrained Object Segmentation Using GrabCut Based on Automatic Generation of Initial Boundary

  • 투고 : 2012.11.09
  • 심사 : 2013.03.15
  • 발행 : 2013.03.28
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초록

Foreground estimation in object segmentation has been an important issue for last few decades. In this paper we propose a GrabCut based automatic foreground estimation method using block clustering. GrabCut is one of popular algorithms for image segmentation in 2D image. However GrabCut is semi-automatic algorithm. So it requires the user input a rough boundary for foreground and background. Typically, the user draws a rectangle around the object of interest manually. The goal of proposed method is to generate an initial rectangle automatically. In order to create initial rectangle, we use Gabor filter and Saliency map and then we use 4 features (amount of area, variance, amount of class with boundary area, amount of class with saliency map) to categorize foreground and background. From the experimental results, our proposed algorithm can achieve satisfactory accuracy in object segmentation without any prior information by the user.

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참고문헌

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  10. Y. Boycov, M. Jolly, "Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images," In Proc. IEEE Int. Conf. on Computer Vision, In ICCV, 2001, pp. 105-112.
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피인용 문헌

  1. Multi-scale Image Segmentation Using MSER and its Application vol.14, pp.3, 2014, https://doi.org/10.5392/JKCA.2014.14.03.011
  2. Automatic Segmentation of Ultrasound Tomography Image vol.2017, pp.2314-6141, 2017, https://doi.org/10.1155/2017/2059036