Method for Ripeness Classification of Harvested Strawberries using Hue Information of Images Acquired After the Harvest

Abstract: Hakata Amaou is the most popular strawberry in Fukuoka Prefecture. However, Amaou farmers face a significant challenge due to a shortage of labor and successors, primarily caused by an aging workforce. This labor shortage is particularly severe during the harvest season, when work must be completed within a short timeframe. To address this issue, INAK System Co., Ltd. has developed an automatic harvesting system called "Robotsumi," which utilizes image recognition technology. Despite this advancement, the current image recognition method has not yet been able to classify the Amaou strawberries into 10 quality grades. Additionally, the image recognition process is affected by image defects, varying light conditions, and shadows. To overcome these challenges, this study first conducted questionnaires to gather information on the ripeness of harvested strawberries as classified by humans. Based on the questionnaire results, maturity classifications using modes of hue were performed. The discrimination results are verified and reported here.

Jin Sawada, Kohei Arai, Souichiro Tashi, Shigenori Inakazu and Mariko Oda. “Method for Ripeness Classification of Harvested Strawberries using Hue Information of Images Acquired After the Harvest”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.6 (2024). http://dx.doi.org/10.14569/IJACSA.2024.01506140

@article{Sawada2024,
title = {Method for Ripeness Classification of Harvested Strawberries using Hue Information of Images Acquired After the Harvest},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01506140},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01506140},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {6},
author = {Jin Sawada and Kohei Arai and Souichiro Tashi and Shigenori Inakazu and Mariko Oda}
}