DocumentCode :
2482682
Title :
Preliminary study on color based nectarine variety classification
Author :
Font, D. ; Palleja, T. ; Tresanchez, M. ; Teixido, M. ; Palacin, J.
Author_Institution :
Dept. of Comput. Sci. & Ind. Eng., Univ. de Lleida, Lleida, Spain
fYear :
2012
fDate :
13-16 May 2012
Firstpage :
2187
Lastpage :
2190
Abstract :
This work presents a preliminary study on an automatic color based nectarine variety classification system. This system is planned to operate in a fruit packing line in order to contribute to increase the quality of an industrial post-harvesting process by verifying nectarine variety. This proposal is based on the computation of the histogram of the hue, saturation, and value (HSV) skin color description of the nectarines analyzed. The histogram is operated as a fingerprint and used to classify the nectarine varieties by defining a reference database with target varieties. Six different varieties have been analyzed in this preliminary study: one yellowish and five reddish. Results show a classification success of 70% for the yellowish variety whereas two reddish varieties show a very low classification success, 20%. These preliminary results evidence the complexity of the classification problem due to the skin color similarity between varieties and the associated quality production problem as different varieties may differ in taste and/or flesh color.
Keywords :
food products; image colour analysis; packaging; HSV skin color description; associated quality production problem; color based nectarine variety classification; fingerprint; flesh color; fruit packaging line; fruit packing line; industrial post-harvesting process; industrial production; taste color; Correlation; Databases; Fingerprint recognition; Histograms; Image color analysis; Production; Skin; HSV; Pearson´s correlation; histogram; nectarine varieties;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International
Conference_Location :
Graz
ISSN :
1091-5281
Print_ISBN :
978-1-4577-1773-4
Type :
conf
DOI :
10.1109/I2MTC.2012.6229514
Filename :
6229514
Link To Document :
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