NDLI: Extended Phase Field Higher-Order Active Contour Models for Networks : Its Application to Road Network Extraction from VHR Satellite Images

Content Provider	Springer Nature Link
Author	Peng, Ting Jermyn, Ian H. Prinet, Véronique Zerubia, Josiane
Copyright Year	2009
Abstract	This 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.
Starting Page	111
Ending Page	128
Page Count	18
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	88
Issue Number	1
e-ISSN	15731405
Language	English
Publisher	Springer US
Publisher Date	2009-10-24
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Active contour Phase field Shape prior Parameter analysis Remote sensing Road network extraction Pattern Recognition Image Processing and Computer Vision Artificial Intelligence (incl. Robotics) Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Higher Order Active Contours

Extended phase field higher-order active contour models for networks

Higher-Order Active Contour Energies for Gap Closure

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

From Images to Shape Models for Object Detection

Contour Grouping Based on Contour-Skeleton Duality

New higher-order active contour models, shape priors, and multiscale analysis: their application to road network extraction from very high resolution satellite images

A Gibbs Point Process for Road Extraction from Remotely Sensed Images

Shape, Contour and Grouping in Computer Vision

Extended Phase Field Higher-Order Active Contour Models for Networks : Its Application to Road Network Extraction from VHR Satellite Images

Similar Documents

Higher Order Active Contours

Extended phase field higher-order active contour models for networks

Higher-Order Active Contour Energies for Gap Closure

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

From Images to Shape Models for Object Detection

Contour Grouping Based on Contour-Skeleton Duality

New higher-order active contour models, shape priors, and multiscale analysis: their application to road network extraction from very high resolution satellite images

A Gibbs Point Process for Road Extraction from Remotely Sensed Images

Shape, Contour and Grouping in Computer Vision

Extended Phase Field Higher-Order Active Contour Models for Networks : Its Application to Road Network Extraction from VHR Satellite Images