Abstract
Figure-Ground segmentation is a fundamental problem in computer vision. Active contours in the form of snakes, balloons, and level-set modeling techniques have been proposed that satisfactorily address this question for certain applications, but require manual initialization, do not always perform well near sharp protrusions or indent ations, or often cross gaps. We propose an approach inspired by these methods and a shock-based representation of shape. Since initially it is not clear where the objects or their parts are, they are hypothesized in the form of fourth order shocks randomly initialized in homogeneous areas of images which then form evolving contours, or bubbles, which grow, shrink, merge, split and disappear to capture the objects in the image. In the homogeneous areas of the image bubbles deform by a reaction-diffusion process. In the inhomogeneous areas, indicated by differential properties computed from low-level processes such as edge-detection, texture, optical-flow and stereo, etc., bubbles do not deform. As such, the randomly initialized bubbles integrate low-level information, and in the process segment figures from ground. The bubble technique does not require manual initialization, integrates a variety of visual information, and deals with gaps of information to capture objects in an image, as illustrated on several MRI and ultrasound images in 2D and 3D.1.
The authors gratefully acknowledge the support of NSF under grant IRI-9305630.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
V. Caselles, F. Catte, T. Coll, and F. Dibos. A geometric model for active contours in image processing. Technical Report No 9210, CEREMADE, 1992.
L. D. Cohen. On active contour models. CVGIP, 53: 211–218, 1991.
M. Kass, A. Witkin, and D. Terzopoulos. Snakes: Active contour models. IJCV, 1: 321–331, 1987.
B. B. Kimia, A. R. Tannenbaum, and S. W. Zucker. Toward a computational theory of shape: An overview. In ECCV, Antibes, France, 1990.
B. B. Kimia, A. R. Tannenbaum, and S. W. Zucker: Shapes, shocks, and deformations, I. IJCV,To Appear.
R. Malladi, J. A. Sethian, and B. C. Vemuri. Evolutionary fronts for topology-independent shape modelling and recovery. In 11CCV, pages 3–13, 1994.
S. Osher and J. Sethian. Fronts propagating with curvature dependent speed. Journal of Computational Physics, 79: 12–49, 1988.
H. Tek and B. B. Kimia. Shock-based reaction-diffusion bubbles for image segmentation. Technical Report LEMS-138, Brown Unversity, August, 1994.
H. Tek and B. B. Kimia. 3D medical image segmentation.Brown U. TR, Jan 95.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1995 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tek, H., Kimia, B.B. (1995). Shock-Based Reaction-Diffusion Bubbles for Image Segmentation. In: Ayache, N. (eds) Computer Vision, Virtual Reality and Robotics in Medicine. CVRMed 1995. Lecture Notes in Computer Science, vol 905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49197-2_55
Download citation
DOI: https://doi.org/10.1007/978-3-540-49197-2_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-59120-7
Online ISBN: 978-3-540-49197-2
eBook Packages: Springer Book Archive