Improving 3D reconstruction quality for root phenotyping: assessing the impact of camera calibration and imaging parameters

Abstract

Accurate 3D reconstruction is essential for high-throughput plant phenotyping, particularly for studying complex structures such as root systems. While photogrammetry and Structure from Motion (SfM) techniques have become widely used for 3D root imaging, the camera settings used are often underreported in studies, and the impact of camera calibration on model accuracyccu remains largely underexplored in plant science. In this study, we systematically evaluate the effects of focus, aperture, exposure time, and gain settings on the quality of 3D root models made with a multi-camera scanning system. We show through a series of experiments that calibration significantly improves model quality, with focus misalignment and shallow depth of field (DoF) being the most important factors affecting reconstruction accuracy. Our results further show that proper calibration has a greater effect on reducing noise than filtering it during post-processing, emphasizing the importance of optimizing image acquisition rather than relying solely on computational corrections. This work improves the repeatability and accuracy of 3D root imaging for phenotyping pipelines by giving useful calibration guidelines. This leads to better trait quantification for use in crop research and plant breeding in downstream analysis.

Plant phenotyping relevance

根の3D画像フェノタイピングにおけるカメラ校正・撮像条件を体系的に評価し、再構成精度と再現性を改善する技術指針を提示しており、フェノタイプ取得手法が研究の中心である。

Code and data availability

The paper states all data are deposited in the BioImage Archive (10.6019/S-BIAD1690), which would be a paper-specific public asset, but that URL/DOI is not among the allowed_urls, so it cannot be listed. The only URLs present in the supplied blocks (CloudCompare, PyntCloud) are generic third-party libraries, not author

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