Vertices and corners: a maximum likelihood approach

Raashid Malik; Siu So

doi:10.1117/12.150176

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20 August 1993 Vertices and corners: a maximum likelihood approach

Raashid Malik, Siu So

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Proceedings Volume 2055, Intelligent Robots and Computer Vision XII: Algorithms and Techniques; (1993) https://doi.org/10.1117/12.150176
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States

Abstract

Scenes of polyhedral objects may be accurately represented in 2-D using line sketches. An aim of low level image processing is to generate useful binary images from grey scale images. The binary images generated by enhancement/threshold edge detectors are usually unrefined outlines of the underlying 3-D scene. Such images must be further processed to isolate and identify region boundaries; which, in the case of polyhedra, consist of line segments. The intersection or connection points of these line segments are known as vertices or corners. The work reported in this paper employs a decision theoretic approach to detect vertices in grey scale images.

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Raashid Malik and Siu So "Vertices and corners: a maximum likelihood approach", Proc. SPIE 2055, Intelligent Robots and Computer Vision XII: Algorithms and Techniques, (20 August 1993); https://doi.org/10.1117/12.150176

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