Improving watersheds image segmentation method with graph theory

Weili Yang; Lei Guo; Tianyun Zhao; Guchu Xiao

doi:10.1109/ICIEA.2007.4318872

Improving watersheds image segmentation method with graph theory

Weili Yang, Lei Guo, Tianyun Zhao, Guchu Xiao

School of Automation

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

This paper presents a new image segmentation method -FWTN (First Watershed Then Normalized cut) based on Watersheds and Graph Theory to solve the over-segmentation problem of watersheds. FWTN firstly uses Normalized Cut to segment between regions after applying watersheds, and then generates the final segmented images. The algorithm can successfully solve over-segmentation problem, and at the same time improve the NP-hard problem of Normalized Cut Experimental results show that FWTN is efficient and practical for image segmentation.

Original language	English
Title of host publication	ICIEA 2007
Subtitle of host publication	2007 Second IEEE Conference on Industrial Electronics and Applications
Pages	2550-2553
Number of pages	4
DOIs	https://doi.org/10.1109/ICIEA.2007.4318872
State	Published - 2007
Event	2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007 - Harbin, China Duration: 23 May 2007 → 25 May 2007

Publication series

Name	ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications

Conference

Conference	2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007
Country/Territory	China
City	Harbin
Period	23/05/07 → 25/05/07

Keywords

Graph theory
Image segmentation
Normalized cut
Watersheds

Access to Document

10.1109/ICIEA.2007.4318872

Cite this

@inproceedings{c4aacc8217c243bdbd1d4141cfb35c44,

title = "Improving watersheds image segmentation method with graph theory",

abstract = "This paper presents a new image segmentation method -FWTN (First Watershed Then Normalized cut) based on Watersheds and Graph Theory to solve the over-segmentation problem of watersheds. FWTN firstly uses Normalized Cut to segment between regions after applying watersheds, and then generates the final segmented images. The algorithm can successfully solve over-segmentation problem, and at the same time improve the NP-hard problem of Normalized Cut Experimental results show that FWTN is efficient and practical for image segmentation.",

keywords = "Graph theory, Image segmentation, Normalized cut, Watersheds",

author = "Weili Yang and Lei Guo and Tianyun Zhao and Guchu Xiao",

year = "2007",

doi = "10.1109/ICIEA.2007.4318872",

language = "英语",

isbn = "1424407370",

series = "ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications",

pages = "2550--2553",

booktitle = "ICIEA 2007",

note = "2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007 ; Conference date: 23-05-2007 Through 25-05-2007",

}

Yang, W, Guo, L, Zhao, T & Xiao, G 2007, Improving watersheds image segmentation method with graph theory. in ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications., 4318872, ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications, pp. 2550-2553, 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007, Harbin, China, 23/05/07. https://doi.org/10.1109/ICIEA.2007.4318872

Improving watersheds image segmentation method with graph theory. / Yang, Weili; Guo, Lei; Zhao, Tianyun et al.
ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications. 2007. p. 2550-2553 4318872 (ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Improving watersheds image segmentation method with graph theory

AU - Yang, Weili

AU - Guo, Lei

AU - Zhao, Tianyun

AU - Xiao, Guchu

PY - 2007

Y1 - 2007

N2 - This paper presents a new image segmentation method -FWTN (First Watershed Then Normalized cut) based on Watersheds and Graph Theory to solve the over-segmentation problem of watersheds. FWTN firstly uses Normalized Cut to segment between regions after applying watersheds, and then generates the final segmented images. The algorithm can successfully solve over-segmentation problem, and at the same time improve the NP-hard problem of Normalized Cut Experimental results show that FWTN is efficient and practical for image segmentation.

AB - This paper presents a new image segmentation method -FWTN (First Watershed Then Normalized cut) based on Watersheds and Graph Theory to solve the over-segmentation problem of watersheds. FWTN firstly uses Normalized Cut to segment between regions after applying watersheds, and then generates the final segmented images. The algorithm can successfully solve over-segmentation problem, and at the same time improve the NP-hard problem of Normalized Cut Experimental results show that FWTN is efficient and practical for image segmentation.

KW - Graph theory

KW - Image segmentation

KW - Normalized cut

KW - Watersheds

UR - http://www.scopus.com/inward/record.url?scp=35248828075&partnerID=8YFLogxK

U2 - 10.1109/ICIEA.2007.4318872

DO - 10.1109/ICIEA.2007.4318872

M3 - 会议稿件

AN - SCOPUS:35248828075

SN - 1424407370

SN - 9781424407378

T3 - ICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications

SP - 2550

EP - 2553

BT - ICIEA 2007

T2 - 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007

Y2 - 23 May 2007 through 25 May 2007

ER -

Improving watersheds image segmentation method with graph theory

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Keywords

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