Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Coupling kinetics of the photorefractive hologram.

Applied optics·2010
Same author

Performance of a phase-transformed input joint transform correlator.

Applied optics·2010
Same author

Kinoform-based Nipkow disk for a confocal microscope.

Applied optics·2010
Same author

Interferometric atmospheric refractive-index environmental monitor.

Applied optics·2010
Same author

Temperature-compensated fiber specklegram strain sensing with an adaptive joint transform correlator.

Applied optics·2010
Same author

Multilayer associative memory and its hybrid optical implementation.

Applied optics·2010
Same journal

Gaussian-modulated continuous-variable quantum key distribution over 60 km fiber using an integrated silicon photonic receiver.

Optics letters·2026
Same journal

E2E-OCT: end-to-end joint learning model using optical coherence tomography images for vocal cord leukoplakia diagnosis.

Optics letters·2026
Same journal

Holographic generation of panoramic 3D scenes by concave ellipsoidal mirror reflection.

Optics letters·2026
Same journal

Dual-pilot phase recovery with pair-wise maximum-ratio combining for coherent PONs.

Optics letters·2026
Same journal

Mapping the whispering gallery modes of a CaF<sub>2</sub> disk resonator with half-tapered fibers to estimate the fundamental mode volume.

Optics letters·2026
Same journal

Quantitative estimation of deep-subwavelength scale via dark-field scattering axial energy concentration decay profiles.

Optics letters·2026
See all related articles

Related Experiment Video

Updated: Jun 20, 2026

Patterned Photostimulation with Digital Micromirror Devices to Investigate Dendritic Integration Across Branch Points
09:30

Patterned Photostimulation with Digital Micromirror Devices to Investigate Dendritic Integration Across Branch Points

Published on: March 2, 2011

Microcomputer-based programmable optical correlator for automatic pattern recognition and identification.

F T Yu1, J E Ludman

  • 1Department of Electrical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.

Optics Letters
|September 5, 2009
PubMed
Summary
This summary is machine-generated.

A novel microcomputer-based programmable optical correlator (MPOC) enables real-time pattern recognition. This system utilizes advanced spatial light modulators for efficient joint-transform correlation, offering programmable processing for complex information.

More Related Videos

Implementation of a Nonlinear Microscope Based on Stimulated Raman Scattering
09:13

Implementation of a Nonlinear Microscope Based on Stimulated Raman Scattering

Published on: July 6, 2019

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
14:58

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

Published on: June 2, 2010

Related Experiment Videos

Last Updated: Jun 20, 2026

Patterned Photostimulation with Digital Micromirror Devices to Investigate Dendritic Integration Across Branch Points
09:30

Patterned Photostimulation with Digital Micromirror Devices to Investigate Dendritic Integration Across Branch Points

Published on: March 2, 2011

Implementation of a Nonlinear Microscope Based on Stimulated Raman Scattering
09:13

Implementation of a Nonlinear Microscope Based on Stimulated Raman Scattering

Published on: July 6, 2019

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
14:58

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

Published on: June 2, 2010

Area of Science:

  • Optics and Photonics
  • Computer Science
  • Image Processing

Background:

  • Traditional pattern recognition methods often lack real-time processing capabilities.
  • Efficiently correlating large amounts of spatial information remains a challenge.

Purpose of the Study:

  • To propose and evaluate a microcomputer-based programmable optical correlator (MPOC) for automatic pattern recognition.
  • To demonstrate the real-time joint-transform correlation capability of the proposed system.

Main Methods:

  • Development of a MPOC integrating a microcomputer with an optical processing system.
  • Utilization of a programmable magneto-optic spatial light modulator and a liquid-crystal light valve.
  • Implementation of a real-time joint-transform correlation algorithm.

Main Results:

  • The MPOC demonstrates real-time programmable processing for large space-bandwidth-product information.
  • Feasibility study confirms the effectiveness of the proposed optical correlator design.
  • Successful joint-transform correlation operations were achieved.

Conclusions:

  • The MPOC offers a powerful solution for real-time automatic pattern recognition and identification.
  • The integration of microcomputer control with optical processing provides significant advantages.
  • The proposed technique is viable for handling complex, high-volume data in pattern recognition applications.