Shape Analysis with Geometric Primitives

Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 2)

Abstract

In this chapter, a unifying framework is presented for analyzing shapes using geometric primitives. It requires both a model of shapes and a model of geometric primitives. We deliberately choose to explore the most general form of shapes through the notion of connected components in a binary image. According to this choice, we introduce geometric primitives for straightness and circularity which are adapted to thick elements. Starting from a model (the tangential cover) which emerged in the digital geometry community we show how to use Constrained Delaunay Triangulation to represent all shapes as a connected path well adapted to the recognition of geometric primitives. We moreover describe how to map our framework into the class of circular arc graphs. Using this mapping we present a multi-primitives analysis which is suitable for self-organizing a shape with respect to prescribed geometric primitives. Further work and open problems conclude the chapter.

Keywords

Point Index Steiner Point Open Node Geometric Primitive Constrain Delaunay Triangulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.IGCNC - EA 2782Clermont Université, Université d’AuvergneClermont-FerrandFrance

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