Abstract book (pdf) - ICPR 2010

WeCT3 Dolmabahçe Hall A
Active Contours and Related Methods Regular Session
Session chair: Burkhardt, Hans (Univ. of Freiburg)
15:40-16:00, Paper WeCT3.1
Level Set based Segmentation using Local Feature Distribution
Xie, Xianghua, Swansea Univ.
We propose a level set based framework to segment textured images. The snake deforms in the image domain in searching
for object boundaries by minimizing an energy functional, which is defined based on dynamically selected local distribution
of orientation invariant features. We also explore the user initialization to simplify the segmentation and improve accuracy.
Experimental results on both synthetic and real data show significant improvements compared to direct modeling of filtering
responses or piecewise constant modeling.
16:00-16:20, Paper WeCT3.2
Mean Shift Gradient Vector Flow: A Robust External Force Field for 3D Active Surfaces
Keuper, Margret, Univ. of Freiburg
Padeken, Jan, Max-Planck-Inst. of Immunobiology
Heun, Patrick, Max-Planck-Inst. of Immunobiology
Burkhardt, Hans, Univ. of Freiburg
Ronneberger, Olaf, Univ. of Freiburg
Gradient vector flow snakes are a very common method in bio-medical image segmentation. The use of gradient vector flow
herein brings some major advantages like a large capture range and a good adaption of the snakes in concave regions. In
some cases though, the application of gradient vector flow can also have undesired effects, e.g. if only parts of an image are
strongly blurred, the remaining weak gradients will be smoothed away. Also, large gradients resulting from small but bright
image structures usually have strong impact on the overall result. To tackle this problem, we present an improvement of the
gradient vector flow, using the mean shift procedure and show its advantages on the segmentation of 3D cell nuclei.
16:20-16:40, Paper WeCT3.3
Adaptive Diffusion Flow for Parametric Active Contours
Wu, Yuwei, Beijing Inst. of Tech.
Wang, Yuanquan, Beijing Inst. of Tech.
Jia, Yunde, Beijing Inst. of Tech.
This paper proposes a novel external force for active contours, called adaptive diffusion flow (ADF). We reconsider the generative
mechanism of gradient vector flow (GVF) diffusion process from the perspective of image restoration, and exploit a
harmonic hyper surface minimal function to substitute smoothness energy term of GVF for alleviating the possible leakage
problem. Meanwhile, a Laplacian functional is incorporated in the ADF framework to ensure that the vector flow diffuses
mainly along normal direction in homogenous regions of an image. Experiments on synthetic and real images demonstrate
the good properties of the ADF snake, including noise robustness, weak edge preserving, and concavity convergence.
16:40-17:00, Paper WeCT3.4
Using Snakes with Asymmetric Energy Terms for the Detection of Varying-Contrast Edges in SAR Images
Seppke, Benjamin, Univ. of Hamburg
Dreschler-Fischer, Leonie, Univ. of Hamburg
Hübbe, Nathanael, Univ. of Hamburg
Active contour methods like snakes, have become a basic tool in computer vision and image analysis over the last years.
They have proven to be adequate for the task of finding boundary features like broken edges in an image. However, when
applying the basic snake technique to synthetic aperture radar (SAR) remote sensing images, the detection of varying-contrast
edges may not be satisfying. This is caused by the special imaging technique of SAR and the commonly known specklenoise.
In this paper we propose the use of asymmetric external energy terms to cope with this problem. We show first results of the
method for the detection of edges of tidal creeks using an ENVISAT ASAR image. These creeks can be found in the World
Heritage Site Wadden Sea located at the German Bight (North Sea).
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