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