Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color Cameras

Recognition and matching of litchi fruits are critical steps for litchi harvesting robots to successfully grasp litchi. However, due to the randomness of litchi growth, such as clustered growth with uncertain number of fruits and random occlusion by leaves, branches and other fruits, the recognition...

Full description

Bibliographic Details
Main Authors: Chenglin Wang, Yunchao Tang, Xiangjun Zou, Lufeng Luo, Xiong Chen
Format: Article
Language:English
Published: MDPI AG 2017-11-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/17/11/2564
id doaj-994285df3f274a53be5bc299788e4362
record_format Article
spelling doaj-994285df3f274a53be5bc299788e43622020-11-24T21:52:54ZengMDPI AGSensors1424-82202017-11-011711256410.3390/s17112564s17112564Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color CamerasChenglin Wang0Yunchao Tang1Xiangjun Zou2Lufeng Luo3Xiong Chen4Key Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, ChinaSchool of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou 510006, ChinaKey Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, ChinaSchool of Mechanical and Electrical Engineering, Foshan University, Foshan 528000, ChinaKey Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, ChinaRecognition and matching of litchi fruits are critical steps for litchi harvesting robots to successfully grasp litchi. However, due to the randomness of litchi growth, such as clustered growth with uncertain number of fruits and random occlusion by leaves, branches and other fruits, the recognition and matching of the fruit become a challenge. Therefore, this study firstly defined mature litchi fruit as three clustered categories. Then an approach for recognition and matching of clustered mature litchi fruit was developed based on litchi color images acquired by binocular charge-coupled device (CCD) color cameras. The approach mainly included three steps: (1) calibration of binocular color cameras and litchi image acquisition; (2) segmentation of litchi fruits using four kinds of supervised classifiers, and recognition of the pre-defined categories of clustered litchi fruit using a pixel threshold method; and (3) matching the recognized clustered fruit using a geometric center-based matching method. The experimental results showed that the proposed recognition method could be robust against the influences of varying illumination and occlusion conditions, and precisely recognize clustered litchi fruit. In the tested 432 clustered litchi fruits, the highest and lowest average recognition rates were 94.17% and 92.00% under sunny back-lighting and partial occlusion, and sunny front-lighting and non-occlusion conditions, respectively. From 50 pairs of tested images, the highest and lowest matching success rates were 97.37% and 91.96% under sunny back-lighting and non-occlusion, and sunny front-lighting and partial occlusion conditions, respectively.https://www.mdpi.com/1424-8220/17/11/2564litchi recognitionharvesting robotbinocular visionstereo matching
collection DOAJ
language English
format Article
sources DOAJ
author Chenglin Wang
Yunchao Tang
Xiangjun Zou
Lufeng Luo
Xiong Chen
spellingShingle Chenglin Wang
Yunchao Tang
Xiangjun Zou
Lufeng Luo
Xiong Chen
Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color Cameras
Sensors
litchi recognition
harvesting robot
binocular vision
stereo matching
author_facet Chenglin Wang
Yunchao Tang
Xiangjun Zou
Lufeng Luo
Xiong Chen
author_sort Chenglin Wang
title Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color Cameras
title_short Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color Cameras
title_full Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color Cameras
title_fullStr Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color Cameras
title_full_unstemmed Recognition and Matching of Clustered Mature Litchi Fruits Using Binocular Charge-Coupled Device (CCD) Color Cameras
title_sort recognition and matching of clustered mature litchi fruits using binocular charge-coupled device (ccd) color cameras
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2017-11-01
description Recognition and matching of litchi fruits are critical steps for litchi harvesting robots to successfully grasp litchi. However, due to the randomness of litchi growth, such as clustered growth with uncertain number of fruits and random occlusion by leaves, branches and other fruits, the recognition and matching of the fruit become a challenge. Therefore, this study firstly defined mature litchi fruit as three clustered categories. Then an approach for recognition and matching of clustered mature litchi fruit was developed based on litchi color images acquired by binocular charge-coupled device (CCD) color cameras. The approach mainly included three steps: (1) calibration of binocular color cameras and litchi image acquisition; (2) segmentation of litchi fruits using four kinds of supervised classifiers, and recognition of the pre-defined categories of clustered litchi fruit using a pixel threshold method; and (3) matching the recognized clustered fruit using a geometric center-based matching method. The experimental results showed that the proposed recognition method could be robust against the influences of varying illumination and occlusion conditions, and precisely recognize clustered litchi fruit. In the tested 432 clustered litchi fruits, the highest and lowest average recognition rates were 94.17% and 92.00% under sunny back-lighting and partial occlusion, and sunny front-lighting and non-occlusion conditions, respectively. From 50 pairs of tested images, the highest and lowest matching success rates were 97.37% and 91.96% under sunny back-lighting and non-occlusion, and sunny front-lighting and partial occlusion conditions, respectively.
topic litchi recognition
harvesting robot
binocular vision
stereo matching
url https://www.mdpi.com/1424-8220/17/11/2564
work_keys_str_mv AT chenglinwang recognitionandmatchingofclusteredmaturelitchifruitsusingbinocularchargecoupleddeviceccdcolorcameras
AT yunchaotang recognitionandmatchingofclusteredmaturelitchifruitsusingbinocularchargecoupleddeviceccdcolorcameras
AT xiangjunzou recognitionandmatchingofclusteredmaturelitchifruitsusingbinocularchargecoupleddeviceccdcolorcameras
AT lufengluo recognitionandmatchingofclusteredmaturelitchifruitsusingbinocularchargecoupleddeviceccdcolorcameras
AT xiongchen recognitionandmatchingofclusteredmaturelitchifruitsusingbinocularchargecoupleddeviceccdcolorcameras
_version_ 1725874215036387328