First results of combining RGB segments and multi-spectral pixel classes for strawberry ripeness detection

Autonomous harvesting of strawberries is dependent on the detection of fruits and their ripeness. For harvesting in commercial fields, at least unripe, ripe, and overripe fruits must be distinguishable. In this paper, we employ visual image-wise segmentation with multi-spectral pixel-wise ripeness classification on real field recordings. Our results show the feasibility and potential of this combination. Furthermore, we identify problematic parts and necessary improvements.

Authors

Publication Details

Journal
REPOSIT
Published
2025-02-04
DOI
https://doi.org/10.48441/4427.3090
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

First results of combining RGB segments and multi-spectral pixel classes for strawberry ripeness detection

Tim Tiedemann, Matthis Trost, Philipp Meyer, Timo Lange
REPOSIT
Smart Agriculture and AI
article

First results of combining RGB segments and multi-spectral pixel classes for strawberry ripeness detection

Tim Tiedemann, Matthis Trost, Philipp Meyer, Timo Lange
article en

Abstract

Autonomous harvesting of strawberries is dependent on the detection of fruits and their ripeness. For harvesting in commercial fields, at least unripe, ripe, and overripe fruits must be distinguishable. In this paper, we employ visual image-wise segmentation with multi-spectral pixel-wise ripeness classification on real field recordings. Our results show the feasibility and potential of this combination. Furthermore, we identify problematic parts and necessary improvements.

REPOSIT
Openalex Percentile: Top 23%
Smart Agriculture and AI
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First results of combining RGB segments and multi-spectral pixel classes for strawberry ripeness detection — Tim Tiedemann, Matthis Trost, et al. · REPOSIT (2025) | TGRS Research Map | TGRS