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논문 리스트

2013
Unconstrained Object Segmentation Using GrabCut Based on Automatic Generation of Initial Boundary Unconstrained Object Segmentation Using GrabCut Based on Automatic Generation of Initial Boundary
한국콘텐츠학회
김수형 외 1명
논문정보
Publisher
International Journal of Contents
Issue Date
2013-03-01
Keywords
-
Citation
-
Source
-
Journal Title
-
Volume
9
Number
1
Start Page
6
End Page
10
DOI
ISSN
17386764
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.

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이름 소속
김수형 인공지능학부