Abstract
In this paper, we propose an automatic prediction system that can predict strawberry harvesting time, sugar content and acidity simultaneously. To do this, we firstly considered a segmentation algorithm using ellipsoid Hough transform that can automatically segment the real strawberry image. Second, we considered HSV color models and histogram - based color features that can be used to classify three stages of maturation of strawberries. Third, we considered the PSL model, which is a statistical analysis method that can be used to predict sugar content and acidity by stages of ripeness of strawberries. Finally, we conducted experiments using various strawberry measurement data observed in Korea's Gangwon - do Highland to evaluate the performance of the proposed prediction system. From the experimental results, it was found that the proposed prediction system can predict the harvest timing, sugar content and acidity of strawberry relatively accurately.
Original language | English |
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Title of host publication | 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781728132716 |
DOIs | |
State | Published - Jun 2019 |
Event | 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 - JeJu, Korea, Republic of Duration: 23 Jun 2019 → 26 Jun 2019 |
Publication series
Name | 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 |
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Conference
Conference | 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 |
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Country/Territory | Korea, Republic of |
City | JeJu |
Period | 23/06/19 → 26/06/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Feature extraction
- Image segmentation
- Prediction of sugar content and organic acids
- Ripeness stages classification
- Statistical analysis
- Strawberry image