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

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 recog...

Full description

Saved in:
Bibliographic Details
Published inICTACT journal on image and video processing Vol. 4; no. 4; pp. 848 - 852
Main Authors T, Pasupathi, A, Arockia Bazil Raj, J, Arputhavijayaselvi
Format Journal Article
LanguageEnglish
Published ICT Academy of Tamil Nadu 01.05.2014
Subjects
Artificial Neural Networks
Feature Extraction
FPGA
Image Recognition
Spiking Neuron
Online AccessGet full text
ISSN0976-9099
0976-9102
DOI10.21917/ijivp.2014.0122

Cover

More Information
Summary: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.
ISSN:0976-9099
0976-9102
DOI:10.21917/ijivp.2014.0122