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Authors: I-Tzu Chen and Huei-Yung Lin

Affiliation: Department of Electrical Engineering, National Chung Cheng University, Chiayi 621, Taiwan

Keyword(s): Yield Estimation, Maturity Assessment, Object Detection, Object Counting, Multi-object Tracking.

Abstract: This paper presents an image-based approach for the yield estimation of cherry tomatoes. The objective is to assist farmers to quickly evaluate the amount of mature tomatoes which are ready to harvest. The proposed technique consists of machine learning based methods for detection, counting, and maturity assessment using multi-spectral images. A convolutional neural network is used for tomato detection from RGB images, followed by the maturity assessment using spectral image analysis with SVM classification. The multi-object tracking algorithm is incorporated to obtain a unique ID for each tomato to avoid double counting during the camera motion. Experiments carried out on the real scene images acquired in an orchard have demonstrated the effectiveness of the proposed method.

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Paper citation in several formats:
Chen, I. and Lin, H. (2020). Detection, Counting and Maturity Assessment of Cherry Tomatoes using Multi-spectral Images and Machine Learning Techniques. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 759-766. DOI: 10.5220/0008874907590766

@conference{visapp20,
author={I{-}Tzu Chen. and Huei{-}Yung Lin.},
title={Detection, Counting and Maturity Assessment of Cherry Tomatoes using Multi-spectral Images and Machine Learning Techniques},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={759-766},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008874907590766},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - Detection, Counting and Maturity Assessment of Cherry Tomatoes using Multi-spectral Images and Machine Learning Techniques
SN - 978-989-758-402-2
IS - 2184-4321
AU - Chen, I.
AU - Lin, H.
PY - 2020
SP - 759
EP - 766
DO - 10.5220/0008874907590766
PB - SciTePress

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