Optical correlator-neural network hybrid system for many patterns recognition

Manivannan, Nadarajah; Neil, Mark A. A.

doi:10.1109/sisy.2010.5647476

Cited by 4 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One such filter, known as the multiplexed filter, was designed using the direct binary search (DBS) algorithm for multiple character recognition and implemented using PSLM. 12 In this paper, a new kind of application is proposed and demonstrated using the optical correlator-neural network (OCNN) hybrid system. Furthermore, they show that use of binary overlay encoding to input pattern can significantly increase the capacity of the multiplexed filter, i.e., increase the number of patterns that can be multiplexed by a single filter of a given set of specifications.…”

Section: Introductionmentioning

confidence: 99%

Optical correlator-neural networks hybrid system for automatic angle measurement of two-dimensional objects

2012

View full text Add to dashboard Cite

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.Subject terms: rotation angle measurement; optical correlator; binary phase-only matched filter; multiplexed filter; neural networks; direct binary search algorithm; error back propagation algorithm; optical information processing.Paper 111068P

show abstract

Section: Introductionmentioning

confidence: 99%

Optical correlator-neural networks hybrid system for automatic angle measurement of two-dimensional objects

2012

View full text Add to dashboard Cite

show abstract

“…increase the number of patterns matched by a single filter of the same specification 2 . Inclusion of a single layer network to optical correlator with multiplexed filters has further increased the capacity of filter by factor of two 12 .…”

Section: Introductionmentioning

confidence: 99%

Automatic angle measurement of a 2D object using optical correlator-neural networks hybrid system

Manivannan

Neil

2011

Optical Pattern Recognition XXII

View full text Add to dashboard Cite

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.Keywords: optical correlator, binary phase-only matched filter, multiplexed filter, neural networks, direct binary search algorithm, error back propagation algorithm and optical information processing

show abstract

Analysis of coherent optical filter and correlator systems using pixellated spatial light modulators

Neil

Manivannan

2012

IET Optoelectron.

View full text Add to dashboard Cite

Optical correlator-neural network hybrid system for many patterns recognition

Cited by 4 publications

References 5 publications

Optical correlator-neural networks hybrid system for automatic angle measurement of two-dimensional objects

Optical correlator-neural networks hybrid system for automatic angle measurement of two-dimensional objects

Automatic angle measurement of a 2D object using optical correlator-neural networks hybrid system

Analysis of coherent optical filter and correlator systems using pixellated spatial light modulators

Contact Info

Product

Resources

About