We describe the concept of a vision system based on an optoelectronic hardware neural processor. The proposed system is composed of a pulse coupled neural network (PCNN) preprocessor stage that converts an input image into a temporal pulsed pattern. These pulses are inputs to the optical broadcast neural network (OBNN) processor, which classifies the input pattern between a set of reference patterns based on a pattern matching strategy. The PCNN is to provide immunity to the scale, rotation, and translation of objects in the image. The OBNN provides high parallelism and a high speed hardware neural processor.
© 2008 Optical Society of America
Original Manuscript: September 5, 2007
Revised Manuscript: December 21, 2007
Manuscript Accepted: January 3, 2008
Published: February 22, 2008
Vol. 3, Iss. 5 Virtual Journal for Biomedical Optics
Horacio Lamela and Marta Ruiz-Llata, "Image identification system based on an optical broadcast neural network and a pulse coupled neural network preprocessor stage," Appl. Opt. 47, B52-B63 (2008)