| dc.contributor.author |
Font Calafell, Davinia |
| dc.contributor.author |
Tresánchez Ribes, Marcel |
| dc.contributor.author |
Pallejà Cabrè, Tomàs |
| dc.contributor.author |
Teixidó Cairol, Mercè |
| dc.contributor.author |
Martínez Lacasa, Daniel |
| dc.contributor.author |
Moreno Blanc, Javier |
| dc.contributor.author |
Palacín Roca, Jordi |
| dc.date |
2016-07-05T11:23:37Z |
| dc.date |
2014 |
| dc.date |
10000-01-01 |
| dc.identifier |
0168-1699 |
| dc.identifier |
http://hdl.handle.net/10459.1/57364 |
| dc.identifier |
https://doi.org/10.1016/j.compag.2014.01.013 |
| dc.identifier.uri |
http://hdl.handle.net/10459.1/57364 |
| dc.description |
This paper presents an image processing method for in-line automatic and individual nectarine variety
verification in a fruit-packing line based on the use of feature histogram vectors obtained by concatenating
the histograms computed from different color layers of a circular central area of the skin of the nectarines
processed. The verification procedure requires the definition of a small dataset with the feature
histogram vectors corresponding to some reference nectarines (manually selected) whose skin clearly
identifies the variety being processed. The in-line variety verification of each nectarine processed is then
done by computing and comparing its current feature histogram vector with the reference dataset. This
paper compares experimentally different alternatives for computing the feature histogram vectors and
two methods for feature comparison and variety verification. The experimental validation consists of
the automatic in-line processing of nectarine samples from different mixed varieties. The results show
an 86% success rate in the case of an expert human operator and 100% when using feature histogram vectors
computed in the Rg (red and gray) or YR (luminance and normalized red) intensity color layers and
when using correlation to compare the feature vectors. |
| dc.description |
This work was partially funded by the University of Lleida, Indra, the Government of Catalonia (Comisionat per a Universitats i Recerca, Departament d’Innovació, Universitats i Empresa) and the European Social Fund. |
| dc.language |
eng |
| dc.publisher |
Elsevier |
| dc.relation |
Reproducció del document publicat a https://doi.org/10.1016/j.compag.2014.01.013 |
| dc.relation |
Computers and Electronics in Agriculture, 2014, vol. 102, p. 112-119 |
| dc.rights |
(c) Elsevier B.V., 2014 |
| dc.rights |
info:eu-repo/semantics/restrictedAccess |
| dc.subject |
Fruit variety verification |
| dc.subject |
Fruit skin comparison |
| dc.subject |
Fruit analysis |
| dc.subject |
Feature histogram vector |
| dc.title |
An image processing method for in-line nectarine variety verification based on the comparison of skin feature histogram vectors |
| dc.type |
article |
| dc.type |
publishedVersion |
