tailieunhanh - Online tomato sorting based on shape, maturity, size, and surface defects using machine vision
Online sorting of tomatoes according to their features is an important postharvest procedure. The purpose of this research was to develop an efficient machine vision-based experimental sorting system for tomatoes. Relevant sorting parameters included shape (oblong and circular), size (small and large), maturity (color), and defects. | Turkish Journal of Agriculture and Forestry Research Article Turk J Agric For (2013) 37: 62-68 © TÜBİTAK doi: Online tomato sorting based on shape, maturity, size, and surface defects using machine vision Omid Omidi ARJENAKI, Parviz Ahmadi MOGHADDAM*, Asad Moddares MOTLAGH Department of Agricultural Machinery Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran Received: Accepted: Published Online: Printed: Abstract: Online sorting of tomatoes according to their features is an important postharvest procedure. The purpose of this research was to develop an efficient machine vision-based experimental sorting system for tomatoes. Relevant sorting parameters included shape (oblong and circular), size (small and large), maturity (color), and defects. The variables defining shape, maturity, and size of the tomatoes were eccentricity, average of color components, and 2-D pixel area, respectively. Tomato defects include color disorders, growth cracks, sunscald, and early blight. The sorting system involved the use of a CCD camera, a microcontroller, sensors, and a computer. Images were analyzed with an algorithm that was developed using Visual Basic 2008. In order to evaluate the accuracy of the algorithms and system performance, 210 tomato samples were used. Each detection algorithm was applied to all images. Data about the type of each sample image, including healthy or defective, elongated or rounded, small or large, and color, were extracted. Results show that defect detection, shape and size algorithm, and overall system accuracies were , , , and 90%, respectively. System sorting performance was estimated at 2517 tomatoes h–1 with 1 line. Key words: Grading, machine vision, sorting, tomato 1. Introduction Tomato is one of the important products in human nutrition that is consumed by millions of people daily. In addition, this
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