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Internal Generative Mechanism Based Otsu Multilevel Thresholding Segmentation for Medical Brain Images Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Interactive RGB-D Image Segmentation Using Hierarchical Graph Cut and Geodesic Distance

Authors : Ling Ge, Ran Ju, Tongwei Ren, Gangshan Wu

Published in: Advances in Multimedia Information Processing -- PCM 2015

Publisher: Springer International Publishing

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Abstract

In this paper, we propose a novel interactive image segmentation method for RGB-D images using hierarchical Graph Cut. Considering the characteristics of RGB channels and depth channel in RGB-D image, we utilize Euclidean distance on RGB space and geodesic distance on 3D space to measure how likely a pixel belongs to foreground or background in color and depth respectively, and integrate the color cue and depth cue into a unified Graph Cut framework to obtain the optimal segmentation result. Moreover, to overcome the low efficiency problem of Graph Cut in handling high resolution images, we accelerate the proposed method with hierarchical strategy. The experimental results show that our method outperforms the state-of-the-art methods with high efficiency.

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Metadata
Title
Interactive RGB-D Image Segmentation Using Hierarchical Graph Cut and Geodesic Distance
Authors
Ling Ge
Ran Ju
Tongwei Ren
Gangshan Wu
Copyright Year
2015
Book
Advances in Multimedia Information Processing -- PCM 2015

Print ISBN: 978-3-319-24074-9

Electronic ISBN: 978-3-319-24075-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-24075-6_12