Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Optical transforms for objects in natural illumination

Open Access Open Access

Abstract

In earlier work an optoelectronic hybrid consisting of a twin-imaging interferometer with crossed roof prisms, a Fourier transform achromat, a CCD array, and a digital computer was described. Spatial cosinusoidal optical transforms can be recorded for rough objects using bandlimited white light. We describe optical metrology and feature extraction using this system. If we consider an idealized amplitude transmittance t(x,y), the advantage in the white light system is that it measures the spatial transform of |t(x,y)|2. In cases where the phase portion contributes a signal that is of little or no interest, clearly the white light transform can be preferable, say, to a system that measures and transforms t(x,y). We describe two separate experiments. For optical metrology, we measure the film grain scattering from commercially available color negative film of various ISO ratings and at different densities. In a separate series of experiments we measured the optical transform pattern that results from printouts of various digital halftones, i.e., the analog of film grain scattering in the electronic printing industry. Finally, we conclude with a discussion of pattern recognition using this white light system combined with neural network software.

© 1989 Optical Society of America

PDF Article
More Like This
Color Appearances of Objects at High Illuminance in Natural Environment

Tsutomu Shibata and Ronald C. Henry
SaB8 Advances in Color Vision (ACV) 1992

Geometric transformations using binary optics

David A. Zweig, Michael P. Power, Thomas J. Mchugh, and James E. Logue
TUE4 OSA Annual Meeting (FIO) 1989

Detection of linear, low-contrast tracks in noisy images via optical Hough Transform

Shih-Chun Lin and R. Scott Boughton
MX5 OSA Annual Meeting (FIO) 1989

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.