26 August 1996 New method for segmentation and motion field estimation
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Proceedings Volume 2785, Vision Systems: New Image Processing Techniques; (1996); doi: 10.1117/12.248560
Event: Lasers, Optics, and Vision for Productivity in Manufacturing I, 1996, Besancon, France
Abstract
In this paper we investigate a new approach to image sequence processing. In some applications of image processing (medical diagnosis, analysis of physical phenomena . . .) the segmented image and the motion field are both needed. It is physically coherent to suppose that these two kinds of data are linked together, and so it would be an improvement to take their mutual interaction into account: different areas make it possible to define motion boundaries and the motion field constitutes temporal information. This algorithm is based on the use of Markov random fields (MRF) which yield good results in such domains. The use of MRF models in association with a maximum a posteriori (MAP) criterion leads to the minimization of a Hamiltonian which is a non-convex function in this case. In order to avoid local minima, we use a multigrid method to compute this minimum.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frederic Bouchara, Jacques Richou, "New method for segmentation and motion field estimation", Proc. SPIE 2785, Vision Systems: New Image Processing Techniques, (26 August 1996); doi: 10.1117/12.248560; https://doi.org/10.1117/12.248560
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KEYWORDS
Image segmentation

Image processing

Motion estimation

Motion models

Algorithm development

Image processing algorithms and systems

Magnetorheological finishing

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