Abstract
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Article Information:
Graph Cuts Based Image Segmentation with Part-Based Models
Wei Liu and Xuejun Xu
Corresponding Author: Wei Liu
Submitted: May 15, 2012
Accepted: June 08, 2012
Published: January 11, 2013 |
Abstract:
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This study proposed an improved pre-labeling method based on deformable part models and HOG
features for interactive segmentation with graph cuts. Because of the complex appearance of foreground and
background, the result of segmentation is unsatisfactory. Many priors have been introduced into graph cuts to
improve the segmentation results and our work is inspired by the shape prior. In this paper we use the deformable
part-based model and HOG features to pre-label the seeds before the graph cuts algorithm. The user involvement is
reduced and the performance of the graph cuts algorithm is improved at the first iteration. Our assumption is based
on the compact shape. We assume that the area between the center of the part filter and root filter belongs to
foreground. If the area covered by more filters, it will more probably be the foreground. Our results show that our
method can get more accurate result especially the appearance of the object and background is similar and the shape
of the object close to rectangle and eclipse.
Key words: Deformable part-based models, graph cuts, image segmentation, , , ,
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Cite this Reference:
Wei Liu and Xuejun Xu, . Graph Cuts Based Image Segmentation with Part-Based Models. Research Journal of Applied Sciences, Engineering and Technology, (02): 491-497.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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