@inproceedings{df27e6b02f1a493eadb1bf52147ede3b,
title = "Plant Leaf Area Estimation via Image Segmentation",
abstract = "In this paper, we propose a method to estimate plant leaf area using image segmentation. In the field of horticulture, destructive analysis is mainly made to measure leaf area, which is required for plant growth measurement. But it has the disadvantage that the plant cannot be used again after analysis. the proposed image based leaf area measurement is non-destructive, and it does not take much time compared with destructive analysis. Leaves in a plant image are first segmented, and then, their correlation to actual leaf area is analyzed. Experimental results show that we can easily predict actual leaf area from plant images.",
keywords = "Leaf area, Linear regression, Plant image, Segmentation",
author = "Lee, {Sang Ho} and Oh, {Myung Min} and Kim, {Jong Ok}",
note = "Funding Information: ACKNOWLEDGMENT This work is supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A4A4079705). Publisher Copyright: {\textcopyright} 2022 IEEE.; 37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022 ; Conference date: 05-07-2022 Through 08-07-2022",
year = "2022",
doi = "10.1109/ITC-CSCC55581.2022.9894907",
language = "English",
series = "ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "996--998",
booktitle = "ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications",
}