DOIONLINE

DOIONLINE NO - IJIEEE-IRAJ-DOI-6019

Publish In
International Journal of Industrial Electronics and Electrical Engineering (IJIEEE)-IJIEEE
Journal Home
Volume Issue
Issue
Volume-4,Issue-10  ( Oct, 2016 )
Paper Title
Spectral Classification in Detection of Foreign Objects Present in Food
Author Name
Sunil N S, Jayanthi P N
Affilition
VLSI design and embedded systems, R.V. College of engineering, Bengaluru, India Dept. of Electronics and Communication engineering, R.V. College of engineering, Bengaluru, India
Pages
84-87
Abstract
The main objective of the present work is to provide a new approach for image recognition using Artificial Neural Networks using spectral classification. Since the different objects possess different spectral properties, collecting the spectral features from each samples and analyzing it for the contaminants detection is the basic idea of the work. Feed forward network is used for the weights calculation and back propagation is used for the error minimization in weights calculated. Training is performed for all the compounds including contaminants. In the testing part compounds with ROI which falls in predefined contaminant boundary which are considered to be contaminants and the execution is done in real time. Keywords— Artificial neural network, spectral properties, spectral features, feed forward network, back propogatio,weights calculation, ROI, Real time.
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