CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
Extended Phase Field Higher-Order Active Contour Models for Networks
Peng, Ting1,2,3; Jermyn, Ian H.3; Prinet, Veronique1,2; Zerubia, Josiane3
AbstractThis paper addresses the segmentation from an image of entities that have the form of a 'network', i.e. the region in the image corresponding to the entity is composed of branches joining together at junctions, e.g. road or vascular networks. We present new phase field higher-order active contour (HOAC) prior models for network regions, and apply them to the segmentation of road networks from very high resolution satellite images. This is a hard problem for two reasons. First, the images are complex, with much 'noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. Second, network regions are complex to model, because they may have arbitrary topology. In particular, we address a limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. We solve this problem by introducing first an additional nonlinear nonlocal HOAC term, and then an additional linear nonlocal HOAC term to improve the computational speed. Both terms allow separate control of branch width and branch curvature, and furnish better prolongation for the same width, but the linear term has several advantages: it is more efficient, and it is able to model multiple widths simultaneously. To cope with the difficulty of parameter selection for these models, we perform a stability analysis of a long bar with a given width, and hence show how to choose the parameters of the energy functions. After adding a likelihood energy, we use both models to extract the road network quasi-automatically from pieces of a QuickBird image, and compare the results to other models in the literature. The state-of-the-art results obtained demonstrate the superiority of our new models, the importance of strong prior knowledge in general, and of the new terms in particular.
KeywordActive Contour Phase Field Shape Prior Parameter Analysis Remote Sensing Road Network Extraction
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000275753900006
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.CASIA, LIAMA, Beijing 100190, Peoples R China
2.CASIA, NLPR, Beijing 100190, Peoples R China
3.INRIA, Project Team Ariana, F-06902 Sophia Antipolis, France
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences;  Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Peng, Ting,Jermyn, Ian H.,Prinet, Veronique,et al. Extended Phase Field Higher-Order Active Contour Models for Networks[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2010,88(1):111-128.
APA Peng, Ting,Jermyn, Ian H.,Prinet, Veronique,&Zerubia, Josiane.(2010).Extended Phase Field Higher-Order Active Contour Models for Networks.INTERNATIONAL JOURNAL OF COMPUTER VISION,88(1),111-128.
MLA Peng, Ting,et al."Extended Phase Field Higher-Order Active Contour Models for Networks".INTERNATIONAL JOURNAL OF COMPUTER VISION 88.1(2010):111-128.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Peng, Ting]'s Articles
[Jermyn, Ian H.]'s Articles
[Prinet, Veronique]'s Articles
Baidu academic
Similar articles in Baidu academic
[Peng, Ting]'s Articles
[Jermyn, Ian H.]'s Articles
[Prinet, Veronique]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Peng, Ting]'s Articles
[Jermyn, Ian H.]'s Articles
[Prinet, Veronique]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.