Estimating the Leaf Area Index of crops through the evaluation of 3D models
| Autor: | Nikolaos Papanikolopoulos, Vassilios Morellas, Dimitris Zermas, David J. Mulla |
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| Rok vydání: | 2017 |
| Předmět: |
Ground truth
010504 meteorology & atmospheric sciences Computer science Point cloud 3d model 02 engineering and technology Agricultural engineering 01 natural sciences Crop 0202 electrical engineering electronic engineering information engineering Production (economics) 020201 artificial intelligence & image processing Leaf area index 0105 earth and related environmental sciences |
| Zdroj: | IROS |
| DOI: | 10.1109/iros.2017.8206517 |
| Popis: | Financial and social elements of modern societies are closely connected to the cultivation of corn. Due to the massive production of corn, deficiencies during the cultivation process directly translate to major financial losses. The early detection and treatment of crops deficiencies is thus a task of great significance. Towards an automated health condition assessment, this study introduces a scheme for the computation of plant health indices. Based on the 3D reconstruction of small batches of corn plants, an alternative to existing cumbersome Leaf Area Index (LAI) estimation methodologies is presented. The use of 3D models provides an elevated information content, when compared to planar methods, mainly due to the reduced loss attributed to leaf occlusions. High resolution images of corn stalks are collected and used to obtain 3D models of plants of interest. Based on the extracted 3D point clouds, an accurate calculation of the Leaf Area Index (LAI) of the plants is performed. An experimental validation (using artificially made corn plants used as ground truth of the LAI estimation), emulating real world scenarios, supports the efficacy of the proposed methodology. The conclusions of this work, suggest a fully automated scheme for information gathering in modern farms capable of replacing current labor intensive procedures, thus greatly impacting the timely detection of crop deficiencies. |
| Databáze: | OpenAIRE |
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