Fruit classification system based on the pressure sensor coupled with support vector machine
<b>Objective:</b> To improve fruit classification accuracy while considering low computational cost and low sensor cost. <b>Methods:</b> A fruit classification system based on capacitive pressure sensor was proposed. The system used support vector machine algorithm with a Gau...
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| Format: | Article |
| Language: | English |
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The Editorial Office of Food and Machinery
2023-10-01
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| Series: | Shipin yu jixie |
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| Online Access: | http://www.ifoodmm.com/spyjxen/article/abstract/20230914 |
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| _version_ | 1850159532770066432 |
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| author | WANG Feifei LIU Peng SUN Fengwei ZHOU Qiong |
| author_facet | WANG Feifei LIU Peng SUN Fengwei ZHOU Qiong |
| author_sort | WANG Feifei |
| collection | DOAJ |
| description | <b>Objective:</b> To improve fruit classification accuracy while considering low computational cost and low sensor cost. <b>Methods:</b> A fruit classification system based on capacitive pressure sensor was proposed. The system used support vector machine algorithm with a Gaussian kernel function (GKF-SVM) to classify fruits. The capacitive pressure sensors used were made of thin copper sheets and a layer of vinyl acetate, and these sensors were fixed to the thumb and index finger of a polyamide spandex glove that simulates a robotic hand. The obtained capacitance value was expressed in the form of digital level, and the data was extracted by data processing software, and the capacitance data was processed by SVM algorithm with kernel functions to determine the category of a fruit. <b>Results:</b> The classification results of 11 kinds of fruits in the designed classification system shown that the smart glove using GKF-SVM algorithm could achieve high accuracy classification of fruits, which could trade off between classification accuracy, calculation cost and low sensor cost according to actual fruit classification needs. <b>Conclusion:</b> The research results can be used to develop electronic systems for fruit classification to improve the fruit classification performance of classification manipulators. |
| format | Article |
| id | doaj-art-6bf37e23bae941eb9c250c05cf51a8e0 |
| institution | OA Journals |
| issn | 1003-5788 |
| language | English |
| publishDate | 2023-10-01 |
| publisher | The Editorial Office of Food and Machinery |
| record_format | Article |
| series | Shipin yu jixie |
| spelling | doaj-art-6bf37e23bae941eb9c250c05cf51a8e02025-08-20T02:23:31ZengThe Editorial Office of Food and MachineryShipin yu jixie1003-57882023-10-01399838810.13652/j.spjx.1003.5788.2023.60072Fruit classification system based on the pressure sensor coupled with support vector machineWANG Feifei0LIU Peng1SUN Fengwei2ZHOU Qiong3 Puyang Medical College, Puyang, Henan 457000 , China Shandong Agricultural University, Tai'an, Shandong 271018 , China Henan Agricultural University, Zhengzhou, Henan 450002 , China Henan University, Zhengzhou, Henan 450046 , China <b>Objective:</b> To improve fruit classification accuracy while considering low computational cost and low sensor cost. <b>Methods:</b> A fruit classification system based on capacitive pressure sensor was proposed. The system used support vector machine algorithm with a Gaussian kernel function (GKF-SVM) to classify fruits. The capacitive pressure sensors used were made of thin copper sheets and a layer of vinyl acetate, and these sensors were fixed to the thumb and index finger of a polyamide spandex glove that simulates a robotic hand. The obtained capacitance value was expressed in the form of digital level, and the data was extracted by data processing software, and the capacitance data was processed by SVM algorithm with kernel functions to determine the category of a fruit. <b>Results:</b> The classification results of 11 kinds of fruits in the designed classification system shown that the smart glove using GKF-SVM algorithm could achieve high accuracy classification of fruits, which could trade off between classification accuracy, calculation cost and low sensor cost according to actual fruit classification needs. <b>Conclusion:</b> The research results can be used to develop electronic systems for fruit classification to improve the fruit classification performance of classification manipulators.http://www.ifoodmm.com/spyjxen/article/abstract/20230914 pressure sensor support vector machine gaussian kernel function fruit classification sorting manipulator |
| spellingShingle | WANG Feifei LIU Peng SUN Fengwei ZHOU Qiong Fruit classification system based on the pressure sensor coupled with support vector machine Shipin yu jixie pressure sensor support vector machine gaussian kernel function fruit classification sorting manipulator |
| title | Fruit classification system based on the pressure sensor coupled with support vector machine |
| title_full | Fruit classification system based on the pressure sensor coupled with support vector machine |
| title_fullStr | Fruit classification system based on the pressure sensor coupled with support vector machine |
| title_full_unstemmed | Fruit classification system based on the pressure sensor coupled with support vector machine |
| title_short | Fruit classification system based on the pressure sensor coupled with support vector machine |
| title_sort | fruit classification system based on the pressure sensor coupled with support vector machine |
| topic | pressure sensor support vector machine gaussian kernel function fruit classification sorting manipulator |
| url | http://www.ifoodmm.com/spyjxen/article/abstract/20230914 |
| work_keys_str_mv | AT wangfeifei fruitclassificationsystembasedonthepressuresensorcoupledwithsupportvectormachine AT liupeng fruitclassificationsystembasedonthepressuresensorcoupledwithsupportvectormachine AT sunfengwei fruitclassificationsystembasedonthepressuresensorcoupledwithsupportvectormachine AT zhouqiong fruitclassificationsystembasedonthepressuresensorcoupledwithsupportvectormachine |