Optoelectronic neural system for vision applications

We present the first implementation, results, and performance analysis of a vision system whose processing core is a prototype hardware neural network based on an optical broadcast architecture. The system captures an im- age by a CMOS image sensor, compares it with a set of sample patterns (classes), and provides an output that indi- cates the class which the input image corresponds to. Due to the optoelectronic neural processor characteristics, the num- ber of classes can be enlarged without penalty on the opera- tion speed of the system. © 2004 Society of Photo-Optical Instru