Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape Matching
Accurate identification of fruits in greenhouse environments is an essential need for the precise functioning of agricultural robots. This study presents a solution to the problem of distinguishing cucumber fruits from their stems and leaves, which often have similar colors in their natural environm...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/5/1884 |
| _version_ | 1797264825295831040 |
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| author | Wenbo Liu Haonan Sun Yu Xia Jie Kang |
| author_facet | Wenbo Liu Haonan Sun Yu Xia Jie Kang |
| author_sort | Wenbo Liu |
| collection | DOAJ |
| description | Accurate identification of fruits in greenhouse environments is an essential need for the precise functioning of agricultural robots. This study presents a solution to the problem of distinguishing cucumber fruits from their stems and leaves, which often have similar colors in their natural environment. The proposed algorithm for cucumber fruit identification relies on color segmentation and form matching. First, we get the boundary details from the acquired image of the cucumber sample. The edge information is described and reconstructed by utilizing a shape descriptor known as the Fourier descriptor in order to acquire a matching template image. Subsequently, we generate a multi-scale template by amalgamating computational and real-world data. The target image is subjected to color conditioning in order to enhance the segmenacktation of the target region inside the HSV color space. Then, the segmented target region is compared to the multi-scale template based on its shape. The method of color segmentation decreases the presence of unwanted information in the target image, hence improving the effectiveness of shape matching. An analysis was performed on a set of 200 cucumber photos that were obtained from the field. The findings indicate that the method presented in this study surpasses conventional recognition algorithms in terms of accuracy and efficiency, with a recognition rate of up to 86%. Moreover, the system has exceptional proficiency in identifying cucumber targets within greenhouses. This attribute renders it a great resource for offering technical assistance to agricultural robots that operate with accuracy. |
| first_indexed | 2024-04-25T00:35:03Z |
| format | Article |
| id | doaj.art-125995f5a49b44248ba0fbe550228753 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-04-25T00:35:03Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-125995f5a49b44248ba0fbe5502287532024-03-12T16:39:20ZengMDPI AGApplied Sciences2076-34172024-02-01145188410.3390/app14051884Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape MatchingWenbo Liu0Haonan Sun1Yu Xia2Jie Kang3School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaSchool of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaSchool of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaSchool of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaAccurate identification of fruits in greenhouse environments is an essential need for the precise functioning of agricultural robots. This study presents a solution to the problem of distinguishing cucumber fruits from their stems and leaves, which often have similar colors in their natural environment. The proposed algorithm for cucumber fruit identification relies on color segmentation and form matching. First, we get the boundary details from the acquired image of the cucumber sample. The edge information is described and reconstructed by utilizing a shape descriptor known as the Fourier descriptor in order to acquire a matching template image. Subsequently, we generate a multi-scale template by amalgamating computational and real-world data. The target image is subjected to color conditioning in order to enhance the segmenacktation of the target region inside the HSV color space. Then, the segmented target region is compared to the multi-scale template based on its shape. The method of color segmentation decreases the presence of unwanted information in the target image, hence improving the effectiveness of shape matching. An analysis was performed on a set of 200 cucumber photos that were obtained from the field. The findings indicate that the method presented in this study surpasses conventional recognition algorithms in terms of accuracy and efficiency, with a recognition rate of up to 86%. Moreover, the system has exceptional proficiency in identifying cucumber targets within greenhouses. This attribute renders it a great resource for offering technical assistance to agricultural robots that operate with accuracy.https://www.mdpi.com/2076-3417/14/5/1884greenhouse environmentsfruit recognitioncolor splitmulti-scaleshape match |
| spellingShingle | Wenbo Liu Haonan Sun Yu Xia Jie Kang Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape Matching Applied Sciences greenhouse environments fruit recognition color split multi-scale shape match |
| title | Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape Matching |
| title_full | Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape Matching |
| title_fullStr | Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape Matching |
| title_full_unstemmed | Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape Matching |
| title_short | Real-Time Cucumber Target Recognition in Greenhouse Environments Using Color Segmentation and Shape Matching |
| title_sort | real time cucumber target recognition in greenhouse environments using color segmentation and shape matching |
| topic | greenhouse environments fruit recognition color split multi-scale shape match |
| url | https://www.mdpi.com/2076-3417/14/5/1884 |
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