A neural network approach to discrimination between defects and calyces in oranges
Abstract
The problem of automatic discrimination among pictures concerning either defects or calyces in oranges is approached. The method here proposed is based on a statistical analysis of the grey-levels and the shape of calyces in the pictures. Some suitable statistical indices are considered and the discriminant function is designed by means of a neural network on the basis of a suitable vector representation of the images. Numerical experiments give 5 misclassifications in a set of 52 images, where only three defects have been classified as calyces.Downloads
Published
Issue
Section
License
The authors retain all rights to the original work without any restrictions.
License for Published Contents
"Le Matematiche" published articlesa are distribuited with Creative Commons Attribution 4.0 International. You are free to copy, distribute and transmit the work, and to adapt the work. You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work).
License for Metadata
"Le Matematiche" published articles metadata are dedicated to the public domain by waiving all publisher's rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.
No Fee Charging
No fee is required to complete the submission/review/publishing process of authors paper.
