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Optics Letters

Optics Letters

| RAPID, SHORT PUBLICATIONS ON THE LATEST IN OPTICAL DISCOVERIES

  • Vol. 20, Iss. 17 — Sep. 1, 1995
  • pp: 1806–1808

Optoelectronic implementation of a diffusion neural network for edge detection

Cheol Soo Cho, Jae Chang Kim, Tae-Hoon Yoon, Ki Gon Nam, Ui Yul Park, and Hua-Kuang Liu  »View Author Affiliations


Optics Letters, Vol. 20, Issue 17, pp. 1806-1808 (1995)
http://dx.doi.org/10.1364/OL.20.001806


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Abstract

We investigate the feasibility of an optoelectronic edge detection system, using a diffusion neural network. The diffusion neural network performs the Gaussian operation efficiently by means of the diffusion process. We apply this in producing the difference-of-two-Gaussians function, which can detect the intensity changes of an image. This system is composed of a spatial light modulator, a two-dimensional image sensor array, and a computer. The processing of the system can be done at a rate of 30 frames/s, making it potentially applicable to systems that require edge detection of an image in real time.

© 1995 Optical Society of America

History
Original Manuscript: April 14, 1995
Published: September 1, 1995

Citation
Cheol Soo Cho, Hua-Kuang Liu, Jae Chang Kim, Tae-Hoon Yoon, Ki Gon Nam, and Ui Yul Park, "Optoelectronic implementation of a diffusion neural network for edge detection," Opt. Lett. 20, 1806-1808 (1995)
http://www.opticsinfobase.org/ol/abstract.cfm?URI=ol-20-17-1806

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