Treffer: Determination of visual quality of tomato paste using computerized inspection system and artificial neural networks

Title:
Determination of visual quality of tomato paste using computerized inspection system and artificial neural networks
Authors:
VELIOGLU, Hasan Murat, BOYACI, Ismail Hakki, KURULTAY, Sefik
Source:
Computers and electronics in agriculture. 77(2):147-154
Publisher Information:
Amsterdam: Elsevier, 2011.
Publication Year:
2011
Physical Description:
print, 3/4 p
Original Material:
INIST-CNRS
Subject Terms:
Agronomy, agriculture, phytopathology, Agronomie, agriculture, phytopathologie, Electronics, Electronique, Computer science, Informatique, Sciences biologiques et medicales, Biological and medical sciences, Sciences biologiques fondamentales et appliquees. Psychologie, Fundamental and applied biological sciences. Psychology, Agronomie. Sciences du sol et productions vegetales, Agronomy. Soil science and plant productions, Apparence physique, Physical appearance, Apariencia física, Concentré tomate, Tomato concentrate, Concentrado tomate, Couleur, Color, Inspection, Inspección, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Observation visuelle, Visual observation, Observación visual, Qualité, Quality, Calidad, Réseau neuronal, Neural network, Red neuronal, Traitement informatique, Computerized processing, Tratamiento informático, Artificial neural networks, Computerized inspection system, Dark speck, Tomato paste
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Namik Kemal University, Vocational College, Meat and Meat Products Technology Programme, Tekirdag 59030, Turkey
Hacettepe University, Engineering Faculty, Food Engineering Department, Ankara 06532, Turkey
Namik Kemal University, Agricultural Faculty, Food Engineering Department, Tekirdag 59030, Turkey
ISSN:
0168-1699
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=24563594
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Agronomy. Soil sciences and vegetal productions
Accession Number:
edscal.24563594
Database:
PASCAL Archive

Weitere Informationen

An artificial neural network (ANN) integrated computerized inspection system (CIS) was developed to determine tomato paste color in CIE L*, a*, and b* color format and the number and size of dark specks which exist in the product. The usability of CIS in the determination of the number and the size of dark specks in tomato paste were investigated by comparing the results of CIS and human inspectors. While the inspectors had difficulties not only in determination of the specks having a diameter less than 0.2 mm but also in correct diameter measurement for all specks, the CIS had good determination and measurement capability. In 99 tomato paste samples, the number of the specks having diameter more than 0.2 mm were found by human inspectors and CIS as 233 and 235, respectively. However, the manual inspection gave inaccurate results for the diameter measurement of the specks. In the color evaluation of the tomato paste, strong correlations (R) were found between the results estimated from ANN-integrated CIS and those obtained from colorimeter (0.889, 0.958, 0.907 and 0.987 for L*, a*, b* and a*/b*, respectively). The whole system is adapted to a graphical user interface (GUI) for use by a non-skilled person working in the tomato paste sector. While manual methods need approximately 5 min, GUI needs 20-25 s to determine, count and classify the dark specks and to measure the product color.