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Distortion and mosaicking of close-up multi-spectral images

Krus, Anne; Valero, Constantino; Ramirez, Juan José; Cruz Ulloa, Christyan; Barrientos, Antonio and Cerro, Jaime (2021) Distortion and mosaicking of close-up multi-spectral images. [Distorsión y mosaicado de imágenes multiespectrales muy próximas.] In: Stafford, John V. (Ed.) Precision Agriculture '21 - Proceedings of the 13th European Conference on Precision Farming, Wageningen Academic Publ., Wageningen, The Neherlands, pp. 363-370.

[thumbnail of Sureveg ECPA2021 CValero.pdf] PDF - Published Version - English
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Summary

In precision agriculture (PA), vegetation indices (VI) are commonly used to evaluate the health of crops with the use of multi-spectral cameras. These are often mounted on drones and used at high altitudes, where the translation of focal points and subsequent changes in perspective do not pose any difficulties. In proximal sensing, however, these translations and distortions pose a significant challenge on data processing. In this work, a Parrot Sequoia camera was mounted at a fixed height of 1.2 m and used at 3 sec and 1.5 sec intervals on an organic strip-cropping field beneath. Reference imaging revealed that the multi-spectral lenses suffer from significant barrel distortion of 30%, while the higher resolution RGB lens has a barely distinguishable 1% pincushion distortion. The subsequent field images were stitched together using an open-source panorama software to automatically detect and correct distortions. The resulting mosaics were then shifted to correct the relative position of the separate lenses, allowing for VI calculation with mm accuracy. This method allows for analysing single plants for inter-crop and even intra-crop variation, allowing the automation of tasks in an organic multicrop environment.


EPrint Type:Conference paper, poster, etc.
Type of presentation:Paper
Keywords:multi-spectral, Parrot Sequoia, lens distortion, image processing, organic farming, strip-crop
Agrovoc keywords:
Language
Value
URI
English
strip cropping
http://aims.fao.org/aos/agrovoc/c_25705
English
robots
http://aims.fao.org/aos/agrovoc/c_25680
English
image processing
http://aims.fao.org/aos/agrovoc/c_37359
Subjects: Crop husbandry > Crop health, quality, protection
Farming Systems > Farm nutrient management
Research affiliation: European Union > CORE Organic Cofund > SUREVEG
Spain > CSIC (Spanish National Research Council)
Spain > Polytechnic University of Madrid
ISBN:978-90-8686-363-1
DOI:10.3920/978-90-8686-916-9
Deposited By: Valero, Constantino
ID Code:43102
Deposited On:26 Jan 2022 15:15
Last Modified:26 Jan 2022 15:15
Document Language:English
Status:Published
Refereed:Peer-reviewed and accepted

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