Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting Process
This study focuses on the segmentation part in the development of a potato-sorting system that utilizes camera input for the segmentation and classification of potatoes. The key challenge addressed is the need for efficient segmentation to allow the sorter to handle a higher volume of potatoes simul...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Foods |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2304-8158/14/7/1131 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850184599033872384 |
|---|---|
| author | Jaka Verk Jernej Hernavs Simon Klančnik |
| author_facet | Jaka Verk Jernej Hernavs Simon Klančnik |
| author_sort | Jaka Verk |
| collection | DOAJ |
| description | This study focuses on the segmentation part in the development of a potato-sorting system that utilizes camera input for the segmentation and classification of potatoes. The key challenge addressed is the need for efficient segmentation to allow the sorter to handle a higher volume of potatoes simultaneously. To achieve this, the study employs a region-based convolutional neural network (R-CNN) approach for the segmentation task, while trying to achieve more precise segmentation than with classic CNN-based object detectors. Specifically, Mask R-CNN is implemented and evaluated based on its performance with different parameters in order to achieve the best segmentation results. The implementation and methodologies used are thoroughly detailed in this work. The findings reveal that Mask R-CNN models can be utilized in the production process of potato sorting and can improve the process. |
| format | Article |
| id | doaj-art-c9a23bdc81ff4c93be2248ec065d4fdc |
| institution | OA Journals |
| issn | 2304-8158 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj-art-c9a23bdc81ff4c93be2248ec065d4fdc2025-08-20T02:17:00ZengMDPI AGFoods2304-81582025-03-01147113110.3390/foods14071131Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting ProcessJaka Verk0Jernej Hernavs1Simon Klančnik2Laboratory for Machining Processes, Faculty of Mechanical Engineering, University of Maribor, Koroška Cesta 46, 2000 Maribor, SloveniaLaboratory for Machining Processes, Faculty of Mechanical Engineering, University of Maribor, Koroška Cesta 46, 2000 Maribor, SloveniaLaboratory for Machining Processes, Faculty of Mechanical Engineering, University of Maribor, Koroška Cesta 46, 2000 Maribor, SloveniaThis study focuses on the segmentation part in the development of a potato-sorting system that utilizes camera input for the segmentation and classification of potatoes. The key challenge addressed is the need for efficient segmentation to allow the sorter to handle a higher volume of potatoes simultaneously. To achieve this, the study employs a region-based convolutional neural network (R-CNN) approach for the segmentation task, while trying to achieve more precise segmentation than with classic CNN-based object detectors. Specifically, Mask R-CNN is implemented and evaluated based on its performance with different parameters in order to achieve the best segmentation results. The implementation and methodologies used are thoroughly detailed in this work. The findings reveal that Mask R-CNN models can be utilized in the production process of potato sorting and can improve the process.https://www.mdpi.com/2304-8158/14/7/1131image segmentationpotato sortingneural networkmask RCNNobject detectionproduction process |
| spellingShingle | Jaka Verk Jernej Hernavs Simon Klančnik Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting Process Foods image segmentation potato sorting neural network mask RCNN object detection production process |
| title | Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting Process |
| title_full | Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting Process |
| title_fullStr | Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting Process |
| title_full_unstemmed | Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting Process |
| title_short | Using a Region-Based Convolutional Neural Network (R-CNN) for Potato Segmentation in a Sorting Process |
| title_sort | using a region based convolutional neural network r cnn for potato segmentation in a sorting process |
| topic | image segmentation potato sorting neural network mask RCNN object detection production process |
| url | https://www.mdpi.com/2304-8158/14/7/1131 |
| work_keys_str_mv | AT jakaverk usingaregionbasedconvolutionalneuralnetworkrcnnforpotatosegmentationinasortingprocess AT jernejhernavs usingaregionbasedconvolutionalneuralnetworkrcnnforpotatosegmentationinasortingprocess AT simonklancnik usingaregionbasedconvolutionalneuralnetworkrcnnforpotatosegmentationinasortingprocess |