A new interpolation algorithm is proposed and demonstrated to perform automatic angle measurement of two-dimensional (2D) objects. The proposed algorithm works in conjunction with optical correlator neural network hybrid architecture (OCNN). The OCNN is trained with a combined algorithm of direct binary search and error back propagation. Input of the OCNN is presented with an image whose angle of rotation is to be measured, and output from the OCNN is fed into the proposed interpolation algorithm, which finally produces the rotation angle of the input image. Results of both computer simulation and experimental set-up are presented for an English alphabetic character as a 2D object. The experimental set-up consists of a real optical correlator using two spatial light modulators for both input and frequency plane representations and a PC based model of a single layer neural network. We obtained very low experimental mean absolute error of 3.18 deg with standard deviation of 2.9 deg.
In this paper a novel method is proposed and demonstrated for automatic rotation angle measurement of a 2D object
using a hybrid architecture, consisting of a 4f optical correlator with a binary phase only multiplexed matched filter and a
single layer neural network. The hybrid set-up can be considered as a two-layer perceptron-like neural network; an
optical correlator is the first layer and the standard single layer neural network is the second layer. The training scheme
used to train the hybrid architecture is a combination of a Direct Binary Search algorithm, to train the optical correlator,
and an Error Back Propagation algorithm, to train the neural network. The aim is to perform the major information
processing by the optical correlator with a small additional processing by the neural network stage. This allows the
system to be used for real-time applications as optics has the inherent ability to process information in a parallel manner
at high speed. The neural network stage gives an extra dimension of freedom so that complicated tasks like automatic
rotation angle measurement can be achieved. Results of both computer simulation and experimental set-up are presented
for rotation angle measurement of an English alphabetic character as a 2D object. The experimental set-up consists of a
real optical correlator using two spatial light modulators for both input and frequency plane representations and a PC
based model of a single layer network.
We have investigated a novel coherent optical correlator architecture for both recognizing and distinguishing between a plurality of patterns using only a single fixed binary phase-only matched filter, referred to here as a multiplexed filter. In order to utilize the filer space effectively we have introduced a novel spread spectrum technique for coding the input patterns, so called overlay encoding, suing a random high frequency binary phase-only mask. We have shown how standard optimization techniques can be used to design a multiplexed filter, which is capable of producing a set of codes in the output plane when the corresponding elements of a set of input patterns are presented in the input plane. The theoretical analysis has been verified experimentally using commercially available ferroelectric liquid crystal spatial light modulators.