Depth-independent segmentation of macroscopic three-dimensional objects encoded in single perspectives of digital holograms.
We present a technique for performing segmentation of macroscopic three-dimensional objects recorded using in-line digital holography. We numerically reconstruct a single perspective of each object at a range of depths. At each point in the digital wavefront we calculate variance about a neighborhood. The maximum variance at each point over all depths is thresholded to classify it as an object pixel or a background pixel. Segmentation results for objects of low and high contrast are presented.
McElhinney
Conor P
CP
Department of Computer Science, National University of Ireland, Maynooth, County Kildare, Ireland. conormce@cs.nuim.ie
McDonald
John B
JB
Castro
Albertina
A
Frauel
Yann
Y
Javidi
Bahram
B
Naughton
Thomas J
TJ