FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

ICTACT Journal on Image and Video Processing ( Volume: 4 , Issue: 4 )

Abstract

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Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

Authors

T. Pasupathi, A. Arockia Bazil Raj, J. Arputhavijayaselvi
Kings College of Engineering, India

Keywords

Image Recognition, Spiking Neuron, FPGA, Artificial Neural Networks, Feature Extraction

Published By
ICTACT
Published In
ICTACT Journal on Image and Video Processing
( Volume: 4 , Issue: 4 )
Date of Publication
May 2014
Pages
848-852

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