Abstract
We describe a method for estimating surface area of three-dimensional binary objects. The method assigns a surface area weight to each 2 × 2 × 2 configuration of voxels. The total surface area is given by a summation of the local area contributions for a digital object. We derive optimal area weights, in order to get an unbiased estimate with minimum variance for randomly oriented planar surfaces. This gives a coefficient of variation (CV) of 1.40% for planar regions. To verify the results and to address the feasibility for area estimation of curved surfaces, the method is tested on convex and non-convex synthetic test objects of increasing size. The algorithm is appealingly simple and uses only a small local neighbourhood. This allows efficient implementations in hardware and/or in parallel architectures.
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Lindblad, J. (2003). Surface Area Estimation of Digitized Planes Using Weighted Local Configurations. In: Nyström, I., Sanniti di Baja, G., Svensson, S. (eds) Discrete Geometry for Computer Imagery. DGCI 2003. Lecture Notes in Computer Science, vol 2886. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39966-7_33
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DOI: https://doi.org/10.1007/978-3-540-39966-7_33
Publisher Name: Springer, Berlin, Heidelberg
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