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Unconstrained Object Segmentation Using GrabCut Based on Automatic Generation of Initial Boundary
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 Title & Authors
Unconstrained Object Segmentation Using GrabCut Based on Automatic Generation of Initial Boundary
Na, In-Seop; Oh, Kang-Han; Kim, Soo-Hyung;
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 Abstract
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.
 Keywords
Gabor filter;Saliency map;Object segmentation;Graph Cut;Foreground;Background;Block Clustering;
 Language
English
 Cited by
1.
MSER을 이용한 다중 스케일 영상 분할과 응용,이진선;오일석;

한국콘텐츠학회논문지, 2014. vol.14. 3, pp.11-21 crossref(new window)
1.
Multi-scale Image Segmentation Using MSER and its Application, The Journal of the Korea Contents Association, 2014, 14, 3, 11  crossref(new windwow)
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