Abstract
Based on machine vision technology, a non-destructive sorting system for full surface information of jujube is designed. The whole machine consists of several parts, including automatic feeding mechanism, sorting mechanism, conveying and attitude adjustment mechanism, grading actuator, detecting and controlling part. Based on theory of mirror reflection principle, an inspection mechanism that can provide the full surface information to the Image processing software is designed to capture a top image, a bottom image and two side images of jujube at the same time, then the problem that the previous sorting system cannot acquire a whole surface information of the red jujube in the condition of high speed transportation is solved. The grading software is designed to process the acquired images in real time, and obtains the surface information such as fruit shape, surface quality and texture. Finally, information fusion technology is used to sort the red jujube with the surface information. The test result shows that the sorting speed of this system is fast, and the sorting accuracy is more than 90%. It can meet the production requirements of detecting and sorting jujube rapidly in an automated way.
Publication Date
5-28-2017
First Page
114
Last Page
118
DOI
10.13652/j.issn.1003-5788.2017.05.024
Recommended Citation
Xiaohua, ZHONG; Yuhua, CAO; Yongqing, ZHANG; and Chengjun, XIAO
(2017)
"Research and implementation of the non-destructive sorting system for full surface information of jujube based on machine vision technology,"
Food and Machinery: Vol. 33:
Iss.
5, Article 24.
DOI: 10.13652/j.issn.1003-5788.2017.05.024
Available at:
https://www.ifoodmm.cn/journal/vol33/iss5/24
References
[1] 白依凡, 贺晓光, 何建国, 等. 红枣自动分级机的研究进展[J]. 宁夏工程技术, 2016(1): 88-92.
[2] 马少辉. 栅条滚筒式红枣分级机改进与试验研究[J]. 中国农机化, 2012(3): 96-98.
[3] 罗雪宁, 彭云发, 代希君, 等. 基于MATLAB的红枣图像处理研究[J]. 农机化研究, 2015(3): 183-186.
[4] 赵杰文, 刘少鹏, 邹小波, 等. 基于支持向量机的缺陷红枣机器视觉识别[J]. 农业机械学报, 2008(3): 113-115, 147.
[5] 刘艳丽, 杜鸿运, 王世璞. 红枣高速在线分级检测系统研发[J]. 中国农机化学报, 2015(5): 142-144.
[6] 王松磊, 刘民法, 何建国, 等. 红枣自动快速无损检测分级机研究[J]. 农业机械学报, 2014(9): 79-83, 95.
[7] 罗华平, 徐贲, 郭玲, 等. 果品分级筛选装置: 中国, 200920277329.7[P]. 2009-12-28.
[8] 田绪顺, 李景彬, 坎杂, 等. 基于机器视觉的红枣双面检测分级装置设计[J]. 食品与机械, 2012, 28(5): 138-140.
[9] 李景彬, 邓向武, 坎杂, 等. 基于机器视觉的干制红枣大小分级方法研究[J]. 农机化研究, 2014(2): 55-59.
[10] 肖爱玲, 潘斌. 基于标记的极半径极值红枣形状识别方法[J]. 农机化研究, 2015(7): 61-65.
[11] 谢忠红, 姬长英, 郭小清, 等. 基于凹点搜索的重叠果实定位检测算法研究[J]. 农业机械学报, 2011(12): 191-196.
[12] 朱煜, 江林佳, 肖玉玲. 材料图像目标粘连点定位与分割方法研究[J]. 南京理工大学学报: 自然科学版, 2008(1): 110-113.
[13] 詹映. 基于机器视觉南疆红枣颜色分级方法研究[D]. 阿拉尔市: 塔里木大学, 2015: 11-12.
[14] 胡小锋, 赵辉. VisualC++/MATLAB图像处理与识别实用案例精选[M]. 北京: 人民邮电出版社, 2004: 131-133.