Image Processing Reference

In-Depth Information

2.1 3D Model Acquisition

The Universidad Nacional de Colombia Sede Manizales has a 3D digitizer VIVID 9i Konica

ation. Since range images cover the object's geometry from a specific point of view, several

shots are needed in order to reconstruct a whole model without occlusions.

FIGURE 1
Konica Minolta VIVID 9i 3D digitizer.

The views acquired with the range scanner must be aligned up into a single coordinate

FIGURE 2
Registration.

Once the views have been registered, the integration process starts. The goal of integration

is to generate a well-defined mesh or data set using the information coming from all the views

seeks to eliminate redundant information in regions with litle variation in the surface, and to

ill small holes in the surface.

FIGURE 3
Integration.

In this study five dental models were used. Eight views were captured in order to construct

each model, with the scanner tilted at 45°, thus achieving good detail within the object of in-

terest. This process was conducted by the research group in Perception and Intelligent Control

3 Point cloud segmentation

In this section, a brief introduction on three different techniques for segmenting point clouds

3.1 RANSAC

The iterative method of RANSAC was proposed by Fischer and Bolles. The technique aims to

estimate the parameters of a mathematical model from a set of observed data using a meth-

od of hypothesis testing. The algorithm is used as a geometric model-based segmentation al-

gorithm, due to its ability to automatically recognize parameterized shapes through the data.

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