1 September 1991 Global minima via dynamic programming: energy minimizing active contours
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Abstract
Reconstruction of objects from a scene may be viewed as a data fitting problem using energy minimizing splines as the basic shape. The process of obtaining the minimum to construct the "best" shape can sometimes be important. Recently, [AWJ9O] brought to light some of the potential problems in the Euler-Lagrangian variational solution proposed in the original formulation [KWT87], and suggested a dynamic programming method. In this paper we further develop the dynamic programming solution. We show that in certain cases, the discrete form of the solution in [AWJ9O] may also produce local minimums, and develop a strategy to avoid this. In the continuous domain, we provide a stronger form of the conditions necessary to derive a solution when the energy depends on the second derivative, as in the case of "active contours."
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sharat Chandran, Tsukasa Maejima, Sanae Miyazaki, "Global minima via dynamic programming: energy minimizing active contours", Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991); doi: 10.1117/12.48441; https://doi.org/10.1117/12.48441
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