Efficient energies and algorithms for parametric snakes

Mathews JACOB; Thierry BLU; Michael UNSER

doi:10.1109/TIP.2004.832919

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Efficient energies and algorithms for parametric snakes

Journal article

Peer reviewed

Efficient energies and algorithms for parametric snakes

Mathews JACOB, Thierry BLU and Michael UNSER

IEEE transactions on image processing, Vol.13(9), pp.1231-1244

2004

DOI: 10.1109/TIP.2004.832919

PMID: 15449585

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http://infoscience.epfl.ch/record/63117View

Open Access

Abstract

Parametric active contour models are one of the preferred approaches for image segmentation because of their computational efficiency and simplicity. However, they have a few drawbacks which limit their performance. In this paper, we identify some of these problems and propose efficient solutions to get around them. The widely-used gradient magnitude-based energy is parameter dependent; its use will negatively affect the parametrization of the curve and, consequently, its stiffness. Hence, we introduce a new edge-based energy that is independent of the parameterization. It is also more robust since it takes into account the gradient direction as well. We express this energy term as a surface integral, thus unifying it naturally with the region-based schemes. The unified framework enables the user to tune the image energy to the application at hand. We show that parametric snakes can guarantee low curvature curves, but only if they are described in the curvilinear abscissa. Since normal curve evolution do not ensure constant arc-length, we propose a new internal energy term that will force this configuration. The curve evolution can sometimes give rise to closed loops in the contour, which will adversely interfere with the optimization algorithm. We propose a curve evolution scheme that prevents this condition.

Signal Processing

Applied Sciences

Pattern recognition. Digital image processing. Computational geometry

Image processing

Telecommunications and information theory

Exact sciences and technology

Information, signal and communications theory

Artificial intelligence

Computer science; control theory; systems

Details

Title: Subtitle: Efficient energies and algorithms for parametric snakes
Creators: Mathews JACOB - Biomedical Imaging Group, Ecole Polytechnique Federale, 1015 Lausanne, Switzerland
Thierry BLU - Biomedical Imaging Group, Ecole Polytechnique Federale, 1015 Lausanne, Switzerland
Michael UNSER - Biomedical Imaging Group, Ecole Polytechnique Federale, 1015 Lausanne, Switzerland
Resource Type: Journal article
Publication Details: IEEE transactions on image processing, Vol.13(9), pp.1231-1244
DOI: 10.1109/TIP.2004.832919
PMID: 15449585
NLM abbreviation: IEEE Trans Image Process
ISSN: 1057-7149
eISSN: 1941-0042
Publisher: Institute of Electrical and Electronics Engineers; New York, NY
Language: English
Date published: 2004
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
Record Identifier: 9984070967302771

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