Design of postharvest infield grading system for navel orange based on
machine vision
1. School of Food and Biological Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China; 2. Citrus Research Institute of CAAS, Chongqing 400712, China
Abstract：To meet the demand of fruit farmers′ timely grading of navel oranges, a set of navel orange postharvest field grading system was designed based on machine vision, which was composed of conveying system, visual system and sorting system. The size of navel orange, the number of surface defects and the defect area were detected by the proposed system. The fruit was automatically graded according to the predetermined comprehensive assessment standard. The experimental results show that the average detection time of single picture is less than 30 ms, and the detection error of size is less than 3% with defect detection rate of 99% and defect area detection error less than 7%. Compared with the traditional detection system, the proposed system has the advantages of high detection speed and compact design, which is suitable for infiled grading of navel orange.
王干, 孙力, 李雪梅, 张明, 吕强, 蔡健荣. 基于机器视觉的脐橙采后田间分级系统设计[J]. 江苏大学学报（自然科学版）, 2017, 38(6): 672-676.
WANG Gan, SUN Li, LI Xue-Mei, ZHANG Ming, 吕Qiang , CAI Jian-Rong. Design of postharvest infield grading system for navel orange based on
machine vision[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2017, 38(6): 672-676.
2017, Vol. 38 
