Characterizing three dimensional open cell structures without segmentation

Joseph H. Nurre; Thomas E. Dufresne; John H. Gideon

doi:10.1117/12.2304394

16 May 2018 Characterizing three dimensional open cell structures without segmentation

Joseph H. Nurre, Thomas E. Dufresne, John H. Gideon

Proceedings Volume 10666, Three-Dimensional Imaging, Visualization, and Display 2018; 106660U (2018) https://doi.org/10.1117/12.2304394
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

Foam cells, particle conglomerates, biological tissue slices and colloidal suspensions are just a few examples of collections that create an image with multiple touching or overlapping regions. The characterization of the open cell size of such a continuous structure is tedious and computationally intensive for large 3D data sets. Typically, it is accomplished by segmenting the cells with a watershed technique and aggregating the statistics of all regions found. This paper provides the mathematical foundation for a newly discovered relationship between the average pixel value of a Euclidean Distance Map (EDM) and the radius of a conic section. The implementation of this relationship allows for a computationally simple and accurate characterization of the aggregate diameter associated with these open cell structures without segmentation.

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Joseph H. Nurre, Thomas E. Dufresne, and John H. Gideon "Characterizing three dimensional open cell structures without segmentation", Proc. SPIE 10666, Three-Dimensional Imaging, Visualization, and Display 2018, 106660U (16 May 2018); https://doi.org/10.1117/12.2304394

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KEYWORDS

Image segmentation

Foam

3D image processing

Error analysis

Quantization

Computed tomography

Image resolution

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