Effect on Quality of 3D Model of Plant with Change in Number and Resolution of Images Used: An Investigation

Paturkar, Abhipray; Gupta, Gourab Sen; Bailey, Donald G.

doi:10.1007/978-981-15-8391-9_28

Cited by 2 publications

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“…For passive techniques, the quality of the point cloud largely depends on the number of images used as well as the plant architecture. A detailed analytical study is provided by Paturkar et al [57] on selecting an appropriate number of images for 3D modeling. This can help to generate a precise point cloud using fewer images.…”

Section: Point Cloudmentioning

confidence: 99%

“…Although the computation time is less, fewer images can generate false points in the 3D point cloud because of the larger change between images. In contrast, a large number of images will result in processing redundant information which will inevitably increase computation time [57]. To obtain an appropriate number of images for precise 3D reconstruction, prior information or manual measurements of plants are required to compare to the corresponding measurements from the 3D model.…”

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Making Use of 3D Models for Plant Physiognomic Analysis: A Review

2021

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Use of 3D sensors in plant phenotyping has increased in the last few years. Various image acquisition, 3D representations, 3D model processing and analysis techniques exist to help the researchers. However, a review of approaches, algorithms, and techniques used for 3D plant physiognomic analysis is lacking. In this paper, we investigate the techniques and algorithms used at various stages of processing and analysing 3D models of plants, and identify their current limiting factors. This review will serve potential users as well as new researchers in this field. The focus is on exploring studies monitoring the plant growth of single plants or small scale canopies as opposed to large scale monitoring in the field.

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Section: Point Cloudmentioning

confidence: 99%

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Making Use of 3D Models for Plant Physiognomic Analysis: A Review

2021

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Plant trait measurement in 3D for growth monitoring

2022

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Background There is a demand for non-destructive systems in plant phenotyping which could precisely measure plant traits for growth monitoring. In this study, the growth of chilli plants (Capsicum annum L.) was monitored in outdoor conditions. A non-destructive solution is proposed for growth monitoring in 3D using a single mobile phone camera based on a structure from motion algorithm. A method to measure leaf length and leaf width when the leaf is curled is also proposed. Various plant traits such as number of leaves, stem height, leaf length, and leaf width were measured from the reconstructed and segmented 3D models at different plant growth stages. Results The accuracy of the proposed system is measured by comparing the values derived from the 3D plant model with manual measurements. The results demonstrate that the proposed system has potential to non-destructively monitor plant growth in outdoor conditions with high precision, when compared to the state-of-the-art systems. Conclusions In conclusion, this study demonstrated that the methods proposed to calculate plant traits can monitor plant growth in outdoor conditions.

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Effect on Quality of 3D Model of Plant with Change in Number and Resolution of Images Used: An Investigation

Cited by 2 publications

References 22 publications

Making Use of 3D Models for Plant Physiognomic Analysis: A Review

Making Use of 3D Models for Plant Physiognomic Analysis: A Review

Plant trait measurement in 3D for growth monitoring

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