In this paper, we describe an algorithm to measure the shape complexity for discrete approximations of planar curves in 2D images and manifold surfaces for 3D triangle meshes. We base our algorithm on shape curvature, and thus we compute shape information as the entropy of curvature. We present definitions to estimate curvature for both discrete curves and surfaces and then formulate our theory of shape information from these definitions. We demonstrate our algorithm with experimental results.
Today, data quality issues are diagnosed and addressed in a piece-meal fashion. The authors recommend a data lifecycle approach and provide a road map, that is more appropriate with the dimensions of Big Data and fits different stages in the analytical workflow.
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