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Proceedings Paper

Segmentation of macroscopic object digital holographic reconstructions using extracted depth information
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Paper Abstract

The nature of digital hologram's allows for the implementation of segmentation process' using volumes of reconstructions as their input, where each reconstruction in the volume is a reconstruction at a different focal plane. Our segmentation technique utilizes extracted focus and shape information. In the case of digital hologram's encoding macroscopic objects, this information is generally obtained using data extraction algorithms applied to a volume of reconstructions. We have developed a three stage segmentation algorithm for macroscopic objects encoded in digital hologram's. This algorithm uses a depth-from-focus technique applied to a set of numerical reconstructions from a single perspective of the digital hologram to extract focus and shape information in the form of a depth map and a maximum focus map. First we estimate the degree of focus at each coordinate. We then calculate a depth map of the scene and segment all object coordinates from background coordinates in the second stage. Finally in the third stage, we perform the segmentation of a digital hologram's reconstruction into independent objects or object regions. A segmentation image is created through applying histogram and image processing algorithms to the depth map. We present results of applying our technique to digital hologram's containing single and multiple macroscopic objects.

Paper Details

Date Published: 25 April 2008
PDF: 9 pages
Proc. SPIE 7000, Optical and Digital Image Processing, 700003 (25 April 2008); doi: 10.1117/12.782776
Show Author Affiliations
C. P. McElhinney, National Univ. of Ireland, Maynooth (Ireland)
B. M. Hennelly, National Univ. of Ireland, Maynooth (Ireland)
J. B. McDonald, National Univ. of Ireland, Maynooth (Ireland)
T. J. Naughton, National Univ. of Ireland, Maynooth (Ireland)
Univ. of Oulu (Finland)

Published in SPIE Proceedings Vol. 7000:
Optical and Digital Image Processing
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal; Frédéric Truchetet, Editor(s)

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