Adam Hennad, Texas A&M University – Corpus Christi

Volumetric Analysis Using 3D Structured Light Scans

Abstract: Volume computations are important for characterization of three-dimensional (3D) objects. In the case of odd-shaped objects, this task is challenging due to the missing symmetry in the geometry of the objects. 3D scanners offer a solution for digitizing the shape of objects for 3D visualization, providing a qualitative representation of the attributes of the scanned sample; however, typical scanners do not offer detailed quantitative information. Quantitative information, such as the volume, when determined non-destructively, offer significant advantage in both research and applications.

In this work, tools and operations are investigated that utilize digital 3D data captured via a 3D structured-light scanner to accurately compute the volume of objects whose shape is not uniform or is otherwise difficult to represent using a simple volume formula. A calibration technique is developed that ensures correct representation of all dimensions in the scans. The scans are then ported to different software tools for analysis. Mesh models are utilized in MATLAB programming tool to develop algorithms for computing the volume of odd-shaped objects and further characterizing their visual attributes.

The calibration technique to create scans with proper dimensions for objects between 3 and 12 centimeters suitable for the specifications of the scanner at hand has been completed. Scanned models have also been successfully exported into MATLAB programming tool. In this presentation, the developed techniques towards 3D volume determination will be shared.

The results of this research are significant in that they will allow quantitative volumetric analysis to be conducted to characterize and monitor varying shapes in both man-made and natural materials. Non-destructive volume as well as other dimensional computations will then allow researchers to assess environmental changes, determine cause-effect relationships, detect surface defects, and characterize agricultural growth. The results can further be extended to other fields including biomedical applications.

Presentation Author(s):
Adam Hennad*

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