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Proceedings Paper

Image preprocessing by neuronlike algorithms
Author(s): Sergey O. Kuznetsov; Irina V. Nuidel; Andrey I. Panfilov; Vladimir G. Yakhno
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Paper Abstract

The problem of image pre-processing by neuron-like algorithms concerns development of systems and methods of image processing in parallel regime. The processing algorithms of grey-tone images to sets of simplified binary images by software of neuron-like filtration (based on the models of homogeneous neural networks) are considered in the paper and partially realized. The time of image processing is calculated. Carrying out of the required set of operations with image is possible according to the convolution function view. The neural network parameters (the type of coupling function and type of element response to the external influence) are selected in accordance with the solution which we want to receive. The program uses function similar to the Mask Convolution function. This function as any other functions basic for image processing are realized in the Intel Corporation `Recognition Primitives Library (RPL) for the Pentium Processor' with great efficiency. Library works under Windows NT. Performed calculations confirm that neuron-like model may be applied for real time image processing using RPL.

Paper Details

Date Published: 1 April 1998
PDF: 7 pages
Proc. SPIE 3402, Optical Information Science and Technology (OIST97): Optical Memory and Neural Networks, (1 April 1998); doi: 10.1117/12.304983
Show Author Affiliations
Sergey O. Kuznetsov, Institute of Applied Physics (Russia)
Irina V. Nuidel, Institute of Applied Physics (Russia)
Andrey I. Panfilov, Institute of Applied Physics (Russia)
Vladimir G. Yakhno, Institute of Applied Physics (Russia)

Published in SPIE Proceedings Vol. 3402:
Optical Information Science and Technology (OIST97): Optical Memory and Neural Networks
Andrei L. Mikaelian, Editor(s)

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