Chhabra, Manish and Reel, Parminder
(2011).
|
Due to copyright restrictions, this file is not available for public download Click here to request a copy from the OU Author. |
| DOI (Digital Object Identifier) Link: | http://dx.doi.org/doi:10.1007/978-3-642-22606-9_8 |
|---|---|
| Google Scholar: | Look up in Google Scholar |
Abstract
Wheat grain quality assessment is important in meeting market requirements. The quality of the wheat can be judge byits length, thickness, width, area, etc. In this paper on the basis of simple mathematical calculations different parameters of a number of wheat grains are calculated. The present paper focused on the classification of wheat grains using morphological. The grain types used in this study were Hard Wheat, Tender Wheat. In this paper the application of neural network is used for assessment of wheat grain. The contours of whole and broken grains have been extracted, precisely normalised and then used as input data for the neural network. The network optimisation has been carried out and then the results have been analysed in the context of response values worked –out by the output neurons.
| Item Type: | Book Chapter |
|---|---|
| Copyright Holders: | 2011 Springer-Verlag |
| ISBN: | 3-642-22605-1, 978-3-642-22605-2 |
| ISSN: | 1865-0929 |
| Extra Information: | 4th International Conference, IC3 2011, Proceedings
Noida, India, August 8-10, 2011 ISSN 1865-0929, e-ISSN 1865-0937 DOI 10.1007/978-3-642-22606-9 |
| Keywords: | wheat quality assessment; image recognition; feature extraction; image segmentation; neural network; MATLAB GUI |
| Academic Unit/Department: | Mathematics, Computing and Technology > Communication and Systems |
| Related URLs: | |
| Item ID: | 34051 |
| Depositing User: | Parminder Reel |
| Date Deposited: | 23 Jul 2012 08:59 |
| Last Modified: | 12 Dec 2012 08:18 |
| URI: | http://oro.open.ac.uk/id/eprint/34051 |
Actions (login may be required)
| View Item | |
| Report issue / request change |