Visualizing concave and convex partitioning of 2D contours

摘要: A new method based on parsing the concavity code is used to partition a digital contour into concave and convex sections. Innovative features of technique include: (1) coerced two-state classification every point or convexity; (2) linguistic explanation for each point's classification; (3) curvature validation via residue (that portion boundary remaining after extraction); (4) preservation original shape; (5) symbolic logic methodology (no floating operations); (6) parameter-free implementation; (7) linear time space complexity. No other currently available partitioning exhibits all these features. The parser achieves by implementing simple notions cumulative curvature, vertex adjacency, shallow absorption, sharing. Concavities convexities are color-coded help disambiguate complex images such as topographic maps radio frequency propagation plots. To gauge product quality, observer may appeal visually validation.