Global minima via dynamic programming: energy minimizing active contours

Sharat Chandran; Tsukasa Maejima; Sanae Miyazaki

doi:10.1117/12.48441

1 September 1991 Global minima via dynamic programming: energy minimizing active contours

Sharat Chandran, Tsukasa Maejima, Sanae Miyazaki

Proceedings Volume 1570, Geometric Methods in Computer Vision; (1991) https://doi.org/10.1117/12.48441
Event: San Diego, '91, 1991, San Diego, CA, United States

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."

Citation Download Citation

Sharat Chandran, Tsukasa Maejima, and Sanae Miyazaki "Global minima via dynamic programming: energy minimizing active contours", Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991); https://doi.org/10.1117/12.48441

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