Abstract

Correlation of two-dimensional digitally recorded holograms is introduced as a novel approach for object recognition without the need for quantitative assessment of the retrieved complex field, based on the fact that a hologram contains the three-dimensional information of the object. Actual objects with different three-dimensional features such as depth and surface roughness are assessed through processing of the correlation of their two-dimensional holograms. Correlation peak values are extracted as a metric to evaluate correlation of three-dimensional objects. The effect of hologram windowing size on correlation of three-dimensional objects is investigated, and improvements in computation time and dynamic range are assessed. Critical figures of merit used for assessment of correlation of images are applied to the correlation of holograms for object recognition.

© 2019 Optical Society of America

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