Academic Journal
Technological Development of Automated Harvesting for Cultivated Button Mushroom Using Image Processing.
| Τίτλος: | Technological Development of Automated Harvesting for Cultivated Button Mushroom Using Image Processing. |
|---|---|
| Συγγραφείς: | Hubay, Csongor, Geösel, András, Horváth, Nóra Hubayné, Géczy, Attila |
| Πηγή: | Periodica Polytechnica: Electrical Engineering & Computer Science; 2024, Vol. 68 Issue 4, p413-423, 11p |
| Θεματικοί όροι: | Python programming language, Fruiting bodies (Fungi), Cultivated mushroom, Image processing, Soil pollution |
| Περίληψη: | The amount of mushrooms cultivated around the world is constantly increasing, and the most commonly consumed species in Europe is the white button mushroom (Agaricus bisporus). Mushroom producers are facing a permanent challenge to provide the labour for harvesting, with increasing wage demands. Due to high market quality requirements, early automatized technologies are currently not able to replace manual picking. Our research therefore aims at facilitating the automated picking of button mushrooms and improving the technology via image processing. We aim to develop a method that can select the right size of mushrooms from field images and produce their picking position. We used Python programming language, along with the OpenCV and NumPy libraries, to implement image processing on real scenario images. The development considered factors such as fused- or overlapping mushroom heads, emergence of mushrooms from under caps, fallen or laterally visible stumps, cover soil contamination, and white mycelia which make detection significantly more difficult. We managed a solution for handling fruiting bodies that extend beyond the edge of the image due to the small field of view. The results indicated that the quality of photographs is crucial for the program's performance, as improper lighting, the presence of shadows. The efficiency of the algorithm was significantly affected by the 82% accuracy of the OpenCV Watershed segmentation algorithm, which in some cases could not separate objects. The program processed the images at an average speed of 0.78 seconds and produced the coordinates with a 92% success rate. [ABSTRACT FROM AUTHOR] |
| Copyright of Periodica Polytechnica: Electrical Engineering & Computer Science is the property of Periodica Polytechnica and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: edb DbLabel: Complementary Index An: 182558372 RelevancyScore: 974 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 973.593017578125 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Technological Development of Automated Harvesting for Cultivated Button Mushroom Using Image Processing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hubay%2C+Csongor%22">Hubay, Csongor</searchLink><br /><searchLink fieldCode="AR" term="%22Geösel%2C+András%22">Geösel, András</searchLink><br /><searchLink fieldCode="AR" term="%22Horváth%2C+Nóra+Hubayné%22">Horváth, Nóra Hubayné</searchLink><br /><searchLink fieldCode="AR" term="%22Géczy%2C+Attila%22">Géczy, Attila</searchLink> – Name: TitleSource Label: Source Group: Src Data: Periodica Polytechnica: Electrical Engineering & Computer Science; 2024, Vol. 68 Issue 4, p413-423, 11p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink><br /><searchLink fieldCode="DE" term="%22Fruiting+bodies+%28Fungi%29%22">Fruiting bodies (Fungi)</searchLink><br /><searchLink fieldCode="DE" term="%22Cultivated+mushroom%22">Cultivated mushroom</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Soil+pollution%22">Soil pollution</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The amount of mushrooms cultivated around the world is constantly increasing, and the most commonly consumed species in Europe is the white button mushroom (Agaricus bisporus). Mushroom producers are facing a permanent challenge to provide the labour for harvesting, with increasing wage demands. Due to high market quality requirements, early automatized technologies are currently not able to replace manual picking. Our research therefore aims at facilitating the automated picking of button mushrooms and improving the technology via image processing. We aim to develop a method that can select the right size of mushrooms from field images and produce their picking position. We used Python programming language, along with the OpenCV and NumPy libraries, to implement image processing on real scenario images. The development considered factors such as fused- or overlapping mushroom heads, emergence of mushrooms from under caps, fallen or laterally visible stumps, cover soil contamination, and white mycelia which make detection significantly more difficult. We managed a solution for handling fruiting bodies that extend beyond the edge of the image due to the small field of view. The results indicated that the quality of photographs is crucial for the program's performance, as improper lighting, the presence of shadows. The efficiency of the algorithm was significantly affected by the 82% accuracy of the OpenCV Watershed segmentation algorithm, which in some cases could not separate objects. The program processed the images at an average speed of 0.78 seconds and produced the coordinates with a 92% success rate. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Periodica Polytechnica: Electrical Engineering & Computer Science is the property of Periodica Polytechnica and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=182558372 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3311/PPee.37570 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 413 Subjects: – SubjectFull: Python programming language Type: general – SubjectFull: Fruiting bodies (Fungi) Type: general – SubjectFull: Cultivated mushroom Type: general – SubjectFull: Image processing Type: general – SubjectFull: Soil pollution Type: general Titles: – TitleFull: Technological Development of Automated Harvesting for Cultivated Button Mushroom Using Image Processing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hubay, Csongor – PersonEntity: Name: NameFull: Geösel, András – PersonEntity: Name: NameFull: Horváth, Nóra Hubayné – PersonEntity: Name: NameFull: Géczy, Attila IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: 2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 20645260 Numbering: – Type: volume Value: 68 – Type: issue Value: 4 Titles: – TitleFull: Periodica Polytechnica: Electrical Engineering & Computer Science Type: main |
| ResultId | 1 |