Potato Sorting in Machine Vision System | Based on Color, Size and Defect Detection

Roya Hassankhani (u. a.)

ISBN 10: 3848434733 / ISBN 13: 9783848434732

Edité par LAP Lambert Academic Publishing, 2012

Potato Sorting in Machine Vision System | Based on Color, Size and Defect Detection | Roya Hassankhani (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783848434732 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 106583288

Synopsis :

Machine vision technique and Image processing are new methods that have various applications in agricultural branch. Machine vision technique is used for grading of wide range of crops. Potatoes (Solanum tuberosum) form one of the major agricultural crops in the world, and are consumed daily by millions of people from diverse cultural backgrounds. Grading and sorting of potatoes ensures that derived products meet the defined grade requirements for sellers, and the expected quality for buyers Qualitative and quantitative sorting of potatoes by means of lighting chamber, camera, frame grabber and computer for catching proper images and processing them is objective of this research. Total sorting accuracy of potatoes was 96.823%. Identification and detection of various defects solely by means of color analysis is difficult because they have envelope in color thresholds. Colored and physical properties of defects are used for grading of them. Grading accuracy of defects was 97.67%.

Présentation de l'éditeur: Machine vision technique and Image processing are new methods that have various applications in agricultural branch. Machine vision technique is used for grading of wide range of crops. Potatoes (Solanum tuberosum) form one of the major agricultural crops in the world, and are consumed daily by millions of people from diverse cultural backgrounds. Grading and sorting of potatoes ensures that derived products meet the defined grade requirements for sellers, and the expected quality for buyers Qualitative and quantitative sorting of potatoes by means of lighting chamber, camera, frame grabber and computer for catching proper images and processing them is objective of this research. Total sorting accuracy of potatoes was 96.823%. Identification and detection of various defects solely by means of color analysis is difficult because they have envelope in color thresholds. Colored and physical properties of defects are used for grading of them. Grading accuracy of defects was 97.67%.

Détails bibliographiques

Titre : Potato Sorting in Machine Vision System | ...
Éditeur : LAP Lambert Academic Publishing
Date d'édition : 2012
Reliure : Taschenbuch
Etat : Neu