Three-dimensional description of symmetric objects from range images

Nicolas Alvertos; Ivan D'Cunha

doi:10.1117/12.25232

1 February 1991 Three-dimensional description of symmetric objects from range images

Nicolas Alvertos, Ivan D'Cunha

Proceedings Volume 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods; (1991) https://doi.org/10.1117/12.25232
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

Abstract

This paper presents a new technique for the three-dimensional recognition of symmetric objects from range images. Beginning from the implicit representation of quadrics a set of ten coefficients is determined for symmetric objects like spheres cones cylinders ellipsoids and parallelepipeds. Instead of using these ten coefficients trying to fit them to smooth surfaces (patches) based on the traditional way of determining curvatures a new approach based on two-dimensional geometry is utilized. For each symmetric object a unique set of two-dimensional curves is obtained from the various angles at which the object is intersected with a plane. Utilizing the same ten coefficients obtained earher and based on the discriminant method each of these curves is classified as a parabola a circle an ellipse or a hyperbola. Each symmetric object is found to possess a unique set of these two-dimensional curves whereby it can be differentiated from the others. In other words it is shown that instead of using the three-dimensional discriminant which involves evaluation of the rank of its matrix it is sufficient to utilize the two-dimensional discriminant which only requires three arithmetic operations. This approach seems to be more accurate and computationally inexpensive compared to the traditional approaches. 1.

Citation Download Citation

Nicolas Alvertos and Ivan D'Cunha "Three-dimensional description of symmetric objects from range images", Proc. SPIE 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods, (1 February 1991); https://doi.org/10.1117/12.25232

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KEYWORDS

Optical spheres

3D image processing

Computer vision technology

Machine vision

Robot vision

Robots

Digital filtering

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